{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c979f719-a7bd-4392-86f9-f699220b2c93",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>STATEFP20</th>\n",
       "      <th>COUNTYFP20</th>\n",
       "      <th>TRACTCE20</th>\n",
       "      <th>GEOID20</th>\n",
       "      <th>NAME20</th>\n",
       "      <th>NAMELSAD20</th>\n",
       "      <th>MTFCC20</th>\n",
       "      <th>FUNCSTAT20</th>\n",
       "      <th>ALAND20</th>\n",
       "      <th>AWATER20</th>\n",
       "      <th>...</th>\n",
       "      <th>P0050002</th>\n",
       "      <th>P0050003</th>\n",
       "      <th>P0050004</th>\n",
       "      <th>P0050005</th>\n",
       "      <th>P0050006</th>\n",
       "      <th>P0050007</th>\n",
       "      <th>P0050008</th>\n",
       "      <th>P0050009</th>\n",
       "      <th>P0050010</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>06</td>\n",
       "      <td>029</td>\n",
       "      <td>004402</td>\n",
       "      <td>06029004402</td>\n",
       "      <td>44.02</td>\n",
       "      <td>Census Tract</td>\n",
       "      <td>G5020</td>\n",
       "      <td>S</td>\n",
       "      <td>1865739</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>26</td>\n",
       "      <td>POLYGON ((-119.33828 35.58143, -119.33827 35.5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>06</td>\n",
       "      <td>047</td>\n",
       "      <td>000802</td>\n",
       "      <td>06047000802</td>\n",
       "      <td>8.02</td>\n",
       "      <td>Census Tract</td>\n",
       "      <td>G5020</td>\n",
       "      <td>S</td>\n",
       "      <td>2321653</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>POLYGON ((-120.59599 37.34121, -120.59596 37.3...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>06</td>\n",
       "      <td>085</td>\n",
       "      <td>501402</td>\n",
       "      <td>06085501402</td>\n",
       "      <td>5014.02</td>\n",
       "      <td>Census Tract</td>\n",
       "      <td>G5020</td>\n",
       "      <td>S</td>\n",
       "      <td>522620</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>POLYGON ((-121.87381 37.34412, -121.87361 37.3...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>06</td>\n",
       "      <td>047</td>\n",
       "      <td>001003</td>\n",
       "      <td>06047001003</td>\n",
       "      <td>10.03</td>\n",
       "      <td>Census Tract</td>\n",
       "      <td>G5020</td>\n",
       "      <td>S</td>\n",
       "      <td>1940304</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>POLYGON ((-120.50491 37.31909, -120.50487 37.3...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>06</td>\n",
       "      <td>019</td>\n",
       "      <td>004303</td>\n",
       "      <td>06019004303</td>\n",
       "      <td>43.03</td>\n",
       "      <td>Census Tract</td>\n",
       "      <td>G5020</td>\n",
       "      <td>S</td>\n",
       "      <td>3799395</td>\n",
       "      <td>33517</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>POLYGON ((-119.84443 36.81038, -119.84443 36.8...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 345 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  STATEFP20 COUNTYFP20 TRACTCE20      GEOID20   NAME20    NAMELSAD20 MTFCC20  \\\n",
       "0        06        029    004402  06029004402    44.02  Census Tract   G5020   \n",
       "1        06        047    000802  06047000802     8.02  Census Tract   G5020   \n",
       "2        06        085    501402  06085501402  5014.02  Census Tract   G5020   \n",
       "3        06        047    001003  06047001003    10.03  Census Tract   G5020   \n",
       "4        06        019    004303  06019004303    43.03  Census Tract   G5020   \n",
       "\n",
       "  FUNCSTAT20  ALAND20  AWATER20  ... P0050002 P0050003 P0050004 P0050005  \\\n",
       "0          S  1865739         0  ...        0        0        0        0   \n",
       "1          S  2321653         0  ...        0        0        0        0   \n",
       "2          S   522620         0  ...        0        0        0        0   \n",
       "3          S  1940304         0  ...        0        0        0        0   \n",
       "4          S  3799395     33517  ...        3        0        3        0   \n",
       "\n",
       "  P0050006 P0050007 P0050008 P0050009 P0050010  \\\n",
       "0        0       26        0        0       26   \n",
       "1        0       12        0        0       12   \n",
       "2        0       11        0        0       11   \n",
       "3        0       11        0        0       11   \n",
       "4        0       35        0        0       35   \n",
       "\n",
       "                                            geometry  \n",
       "0  POLYGON ((-119.33828 35.58143, -119.33827 35.5...  \n",
       "1  POLYGON ((-120.59599 37.34121, -120.59596 37.3...  \n",
       "2  POLYGON ((-121.87381 37.34412, -121.87361 37.3...  \n",
       "3  POLYGON ((-120.50491 37.31909, -120.50487 37.3...  \n",
       "4  POLYGON ((-119.84443 36.81038, -119.84443 36.8...  \n",
       "\n",
       "[5 rows x 345 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# this is for working with census tracts and VTD precincts\n",
    "from shapely.geometry import Point, LineString, Polygon\n",
    "import shapely\n",
    "import geopandas as gpd\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from numpy import random\n",
    "from scipy.stats import norm\n",
    "import math\n",
    "#tractGeomFile = gpd.read_file(\"state_map_files/fl_pl2020_t.shp\")  #Boo!  Only has geometries.  do not use\n",
    "tractPopFile = gpd.read_file(\"state_map_files/ca_pl2020_t.dbf\") #for Texas, need only this file\n",
    "tractPopFile.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a7a90b04-4b48-4ab8-9195-8d953907c3fb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are 9129 popn tracts for CA\n"
     ]
    }
   ],
   "source": [
    "# EXTRACT TRACT GEOMETRIES AND POPULATIONS INTO LISTS, COMPUTE TRACT AREAS\n",
    "# If the population and geometry data are in one file, this should work.\n",
    "STATE = \"CA\"\n",
    "tractGeom = tractPopFile['geometry']  #for some states, replace with tractGeomFile\n",
    "tractPop = tractPopFile['P0010001']\n",
    "tractVAP = tractPopFile['P0030001']   #NEW 3/2/22 - USE VAP\n",
    "# tractPop2 = tractPopFile['P0020001']   #not needed; confirmed that this matches P00100001 exactly\n",
    "tractHisp = tractPopFile['P0040002']   #NEW 3/2/22 - USE VAP\n",
    "tractBlack = tractPopFile['P0030004']  #NEW 3/2/22 - USE VAP\n",
    "nTracts = len(tractPop)\n",
    "print(\"there are {0} popn tracts for {1}\".format(nTracts, STATE) )\n",
    "tractArea = [0.]*nTracts\n",
    "for t in range (0,nTracts) :\n",
    "    tractArea[t] = tractGeom[t].area\n",
    "isSkippedTract = [0] *nTracts  #this will house a temporary list of tracts for manipulation\n",
    "tractPop = tractPop.to_numpy()  #to avoid panda overwrite grousing\n",
    "tractBlack= tractBlack.to_numpy()\n",
    "tractHisp = tractHisp.to_numpy()\n",
    "tractVAP = tractVAP.to_numpy()\n",
    "stateVAP = np.sum(tractVAP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c90b3908-e2e3-46b8-98e5-ae285eca1ee3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this is Hispanic population by total population CA voter-age population\n",
      "state pop= 39538223 VAP pct Hispanic is  0.35953080900720324\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#What is our correlation of Hispanic pop to total pop?\n",
    "print(\"this is Hispanic population by total population \"+STATE,\"voter-age population\")\n",
    "print(\"state pop=\",np.sum(tractPop), \"VAP pct Hispanic is \",np.sum(tractHisp)/np.sum(tractVAP) )\n",
    "fig, ax = plt.subplots()\n",
    "ax.set(xlabel=\"tract Voter Age Population\", ylabel=\"tract Hispanic pop\")\n",
    "x = [0,10000]\n",
    "y = [0,10000]\n",
    "plt.plot(tractVAP, tractHisp, marker='.',linestyle=\"none\")\n",
    "plt.plot(x,y,linestyle = 'dashed')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "237df16d-af87-47ba-acb1-2ef5702c1406",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this is voter-age Black population by total VAP CA\n",
      "total state pop= 39538223 , VAP pct Black is  0.0570202099743067\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#What is our correlation of Black pop to total pop?\n",
    "print(\"this is voter-age Black population by total VAP \"+STATE)\n",
    "print(\"total state pop=\",np.sum(tractPop), \", VAP pct Black is \",np.sum(tractBlack)/np.sum(tractVAP) )\n",
    "fig, ax = plt.subplots()\n",
    "ax.set(xlabel=\"tract VAP\", ylabel=\"tract Black VAP\")\n",
    "x = [0,10000]\n",
    "y = [0,10000]\n",
    "plt.plot(tractVAP, tractBlack, marker='.',linestyle=\"none\")\n",
    "plt.plot(x,y,linestyle = 'dashed')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "10b208af-8eb0-45fa-9dc0-8873eb797200",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this is a histogram of Census tract population for CA\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#for curiosity, let's plot the distribution of populations among tracts\n",
    "n_bins=50\n",
    "print(\"this is a histogram of Census tract population for \"+STATE)        \n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "# We can set the number of bins with the *bins* keyword argument.\n",
    "ax.hist(tractPop, bins=n_bins)\n",
    "plt.show() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4aac60d6-4cce-469b-b075-ad743acda38c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this is population by Census tract for CA\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#What is our distribution of tract populations by area?\n",
    "print(\"this is population by Census tract for \"+STATE)  \n",
    "plt.plot(tractPop, tractArea, marker='.',linestyle=\"none\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f159bf55-a25e-45c0-b7ea-4c21fbce9bb0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'shapely.geometry.polygon.Polygon'> <class 'shapely.geometry.polygon.Polygon'>\n"
     ]
    }
   ],
   "source": [
    "print( type(tractGeom[0]),type(tractGeom[1]) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5e8f8f92-a336-43e5-8ac5-20c657cb5857",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "looking for nonPolygons in census tract data\n",
      "59 3 0.07602628146049996 nonPolygon tract no, pop, area\n",
      "60 0 0.23528077604550024 nonPolygon tract no, pop, area\n",
      "183 3486 0.015889839251500004 nonPolygon tract no, pop, area\n",
      "190 2174 0.0007841577370000847 nonPolygon tract no, pop, area\n",
      "2420 1393 0.00039417031349999485 nonPolygon tract no, pop, area\n",
      "3131 4153 0.00024405907400001245 nonPolygon tract no, pop, area\n",
      "3137 5750 0.0003423576004998158 nonPolygon tract no, pop, area\n",
      "3138 5535 0.0003127899885000581 nonPolygon tract no, pop, area\n",
      "7126 0 0.06901639653200091 nonPolygon tract no, pop, area\n",
      "0.02295177486399969\n",
      "0.046064621668001224\n",
      "7320 0 0.014018558813500519 nonPolygon tract no, pop, area\n",
      "0.0007137218559999444\n",
      "0.010774742401000435\n",
      "0.00253009455650014\n",
      "7374 553 0.13879085878000014 nonPolygon tract no, pop, area\n",
      "7618 0 0.06725813562649952 nonPolygon tract no, pop, area\n",
      "0.0006308005500000153\n",
      "0.013295888545999852\n",
      "0.053331446530499656\n",
      "7624 0 0.08582758568849956 nonPolygon tract no, pop, area\n",
      "8803 2747 0.0005138376849999682 nonPolygon tract no, pop, area\n",
      "1.2383925999994096e-05\n",
      "0.00047850005499999813\n",
      "2.446553000001804e-06\n",
      "2.0507150999974147e-05\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"looking for nonPolygons in census tract data\")\n",
    "notPoly = [0]*nTracts\n",
    "for m in range(nTracts):\n",
    "    if type(tractGeom[m]) != type(tractGeom[1]):  #assuming tract 1 is a single polygon\n",
    "        notPoly[m] = 1\n",
    "        print(m,tractPop[m], tractArea[m], \"nonPolygon tract no, pop, area\")\n",
    "        x = tractGeom[m].centroid.x\n",
    "        y = tractGeom[m].centroid.y\n",
    "        if y > 36.8 :  #let's zoom in on these\n",
    "            for geom in tractGeom[m].geoms :\n",
    "                xg,yg = geom.exterior.xy\n",
    "                print(geom.area)\n",
    "                plt.plot(xg,yg)\n",
    "            plt.text(x+0.0,y+0.01,m,fontsize=9)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a466477e-ed24-49fe-89da-78ebe9306c88",
   "metadata": {},
   "outputs": [],
   "source": [
    "#OK, we will convex-hull 8803 and skip two NW Pacific Ocean tracts. \n",
    "#the other northern ones have no people, so leave them be\n",
    "isSkippedTract = [0]*nTracts\n",
    "isSkippedTract[7618] = 1\n",
    "isSkippedTract[7126] = 1\n",
    "tractGeom[8803] = tractGeom[8803].convex_hull\n",
    "notPoly[8803] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "05759c1a-d866-443c-8ae1-96e8354829c5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "59 3 0.07602628146049996 nonPolygon tract no, pop, area\n",
      "0.0004925252069999553\n",
      "0.038141434318499895\n",
      "0.03107838214800014\n",
      "5.658019999968054e-07\n",
      "0.006313373984999967\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "ready to move on? 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "60 0 0.23528077604550024 nonPolygon tract no, pop, area\n",
      "0.015525463085000074\n",
      "0.1221196343839998\n",
      "0.09763567857650036\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "ready to move on? 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "183 3486 0.015889839251500004 nonPolygon tract no, pop, area\n",
      "1.003827999996256e-06\n",
      "0.015888835423500006\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "ready to move on? 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "190 2174 0.0007841577370000847 nonPolygon tract no, pop, area\n",
      "0.00016340248250010377\n",
      "0.000620755254499981\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "ready to move on? 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2420 1393 0.00039417031349999485 nonPolygon tract no, pop, area\n",
      "0.00039286068349999665\n",
      "1.3096299999981781e-06\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "ready to move on? 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3131 4153 0.00024405907400001245 nonPolygon tract no, pop, area\n",
      "0.0002428934435000197\n",
      "1.165630499992768e-06\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "ready to move on? 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3137 5750 0.0003423576004998158 nonPolygon tract no, pop, area\n",
      "0.0003401567929998575\n",
      "2.2008074999582695e-06\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "ready to move on? 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3138 5535 0.0003127899885000581 nonPolygon tract no, pop, area\n",
      "0.0003122337740000678\n",
      "5.562144999903496e-07\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "ready to move on? 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7126 0 0.06901639653200091 nonPolygon tract no, pop, area\n",
      "7320 0 0.014018558813500519 nonPolygon tract no, pop, area\n",
      "7374 553 0.13879085878000014 nonPolygon tract no, pop, area\n",
      "0.07344283806749989\n",
      "0.06534802071250025\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "ready to move on? 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7618 0 0.06725813562649952 nonPolygon tract no, pop, area\n",
      "7624 0 0.08582758568849956 nonPolygon tract no, pop, area\n",
      "0.018002791168499985\n",
      "0.03951327067949968\n",
      "0.028311523840499894\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "ready to move on? 1\n"
     ]
    }
   ],
   "source": [
    "for m in range(nTracts):\n",
    "    if type(tractGeom[m]) != type(tractGeom[1]):  #assuming tract 1 is a single polygon\n",
    "        print(m,tractPop[m], tractArea[m], \"nonPolygon tract no, pop, area\")\n",
    "        x = tractGeom[m].centroid.x\n",
    "        y = tractGeom[m].centroid.y\n",
    "        if y < 36.8 :  #let's zoom in on these\n",
    "            for geom in tractGeom[m].geoms :\n",
    "                xg,yg = geom.exterior.xy\n",
    "                print(geom.area)\n",
    "                plt.plot(xg,yg)\n",
    "            plt.text(x+0.0,y+0.01,m,fontsize=9)\n",
    "            plt.show()\n",
    "            pause = input(\"ready to move on?\")\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f3432c2b-f3a7-41a6-9c55-331afc6bf955",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "59 3 0.07602628146049996 nonPolygon tract no, pop, area\n",
      "60 0 0.23528077604550024 nonPolygon tract no, pop, area\n",
      "7126 0 0.06901639653200091 nonPolygon tract no, pop, area\n",
      "7320 0 0.014018558813500519 nonPolygon tract no, pop, area\n",
      "7618 0 0.06725813562649952 nonPolygon tract no, pop, area\n",
      "7624 0 0.08582758568849956 nonPolygon tract no, pop, area\n"
     ]
    }
   ],
   "source": [
    "# ok, let's convex_hull all with some pop\n",
    "convexList = [183, 190, 2420, 3131, 3137, 3138, 7374]\n",
    "for cL in range(len(convexList)):\n",
    "    t = convexList[cL]\n",
    "    tractGeom[t] = tractGeom[t].convex_hull\n",
    "    notPoly[t] = 0\n",
    "\n",
    "minTractPop = 10  #now, check that we have no remaining populated nonPoly tracts\n",
    "for m in range(nTracts):\n",
    "    if type(tractGeom[m]) != type(tractGeom[1]):  #assuming tract 1 is a single polygon\n",
    "        print(m,tractPop[m], tractArea[m], \"nonPolygon tract no, pop, area\")\n",
    "        x = tractGeom[m].centroid.x\n",
    "        y = tractGeom[m].centroid.y\n",
    "        if tractPop[m] > minTractPop :  #plot the remaining nonPoly populated tracts\n",
    "            for geom in tractGeom[m].geoms :\n",
    "                xg,yg = geom.exterior.xy\n",
    "                print(geom.area)\n",
    "                plt.plot(xg,yg)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "69edb6b2-7b88-43ca-8017-ff4d271ce3e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#see MD for example of re-assign the tract to its latter polygon\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "72abde7f-085d-4c0a-abe3-29e8d6203b40",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>COUNTY</th>\n",
       "      <th>CNTY_CODE</th>\n",
       "      <th>FIPS_CODE</th>\n",
       "      <th>SRPREC_KEY</th>\n",
       "      <th>SRPREC</th>\n",
       "      <th>ADDIST</th>\n",
       "      <th>CDDIST</th>\n",
       "      <th>SDDIST</th>\n",
       "      <th>BEDIST</th>\n",
       "      <th>G20PREDBID</th>\n",
       "      <th>G20PRERTRU</th>\n",
       "      <th>G20PRELJOR</th>\n",
       "      <th>G20PREGHAW</th>\n",
       "      <th>G20PREAFUE</th>\n",
       "      <th>G20PREPLAR</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Alameda</td>\n",
       "      <td>1</td>\n",
       "      <td>6001</td>\n",
       "      <td>6001481430</td>\n",
       "      <td>481430</td>\n",
       "      <td>20</td>\n",
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       "      <td>POLYGON ((-13591389.953 4534199.875, -13591391...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Alameda</td>\n",
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       "      <td>6001</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Alameda</td>\n",
       "      <td>1</td>\n",
       "      <td>6001</td>\n",
       "      <td>6001430410</td>\n",
       "      <td>430410</td>\n",
       "      <td>20</td>\n",
       "      <td>15</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>POLYGON ((-13591451.086 4533620.113, -13591468...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Alameda</td>\n",
       "      <td>1</td>\n",
       "      <td>6001</td>\n",
       "      <td>6001430500</td>\n",
       "      <td>430500</td>\n",
       "      <td>20</td>\n",
       "      <td>15</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>POLYGON ((-13591463.435 4534097.046, -13591464...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Alameda</td>\n",
       "      <td>1</td>\n",
       "      <td>6001</td>\n",
       "      <td>6001430130</td>\n",
       "      <td>430130</td>\n",
       "      <td>20</td>\n",
       "      <td>15</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>POLYGON ((-13591792.296 4532623.256, -13591794...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    COUNTY CNTY_CODE FIPS_CODE  SRPREC_KEY  SRPREC  ADDIST  CDDIST  SDDIST  \\\n",
       "0  Alameda         1      6001  6001481430  481430      20      15      10   \n",
       "1  Alameda         1      6001  6001430420  430420      20      15      10   \n",
       "2  Alameda         1      6001  6001430410  430410      20      15      10   \n",
       "3  Alameda         1      6001  6001430500  430500      20      15      10   \n",
       "4  Alameda         1      6001  6001430130  430130      20      15      10   \n",
       "\n",
       "   BEDIST  G20PREDBID  G20PRERTRU  G20PRELJOR  G20PREGHAW  G20PREAFUE  \\\n",
       "0       2           0           0           0           0           0   \n",
       "1       2           0           0           0           0           0   \n",
       "2       2           3           1           0           0           0   \n",
       "3       2           1           0           0           0           0   \n",
       "4       2           0           0           0           0           0   \n",
       "\n",
       "   G20PREPLAR                                           geometry  \n",
       "0           0  POLYGON ((-13591389.953 4534199.875, -13591391...  \n",
       "1           0  POLYGON ((-13591791.751 4534039.872, -13591792...  \n",
       "2           0  POLYGON ((-13591451.086 4533620.113, -13591468...  \n",
       "3           0  POLYGON ((-13591463.435 4534097.046, -13591464...  \n",
       "4           0  POLYGON ((-13591792.296 4532623.256, -13591794...  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Now, let's read in the voting data  \n",
    "VTDdbf = gpd.read_file(\"state_map_files/ca_vest_20.dbf\")\n",
    "VTDdbf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4f3b9ddb-b971-472c-a353-521377f95e46",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>COUNTY</th>\n",
       "      <th>CNTY_CODE</th>\n",
       "      <th>FIPS_CODE</th>\n",
       "      <th>SRPREC_KEY</th>\n",
       "      <th>SRPREC</th>\n",
       "      <th>ADDIST</th>\n",
       "      <th>CDDIST</th>\n",
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       "      <td>Alameda</td>\n",
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       "      <td>6001430500</td>\n",
       "      <td>430500</td>\n",
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      "text/plain": [
       "    COUNTY CNTY_CODE FIPS_CODE  SRPREC_KEY  SRPREC  ADDIST  CDDIST  SDDIST  \\\n",
       "0  Alameda         1      6001  6001481430  481430      20      15      10   \n",
       "1  Alameda         1      6001  6001430420  430420      20      15      10   \n",
       "2  Alameda         1      6001  6001430410  430410      20      15      10   \n",
       "3  Alameda         1      6001  6001430500  430500      20      15      10   \n",
       "4  Alameda         1      6001  6001430130  430130      20      15      10   \n",
       "\n",
       "   BEDIST  G20PREDBID  G20PRERTRU  G20PRELJOR  G20PREGHAW  G20PREAFUE  \\\n",
       "0       2           0           0           0           0           0   \n",
       "1       2           0           0           0           0           0   \n",
       "2       2           3           1           0           0           0   \n",
       "3       2           1           0           0           0           0   \n",
       "4       2           0           0           0           0           0   \n",
       "\n",
       "   G20PREPLAR                                           geometry  \n",
       "0           0  POLYGON ((-122.09353 37.67916, -122.09355 37.6...  \n",
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      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "VTDdbf = VTDdbf.to_crs(tractPopFile.crs)  #CA's precinct file is in wrong CRS\n",
    "VTDdbf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "3fe4ceba-8077-4485-ad0a-f8f2a5755040",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20799 0.3509058667735862 17116921 = number of precincts, statewide GOP vote, total Trump+Biden votes\n"
     ]
    }
   ],
   "source": [
    "# Pull VTD geopandas data columns into arrays\n",
    "vtdGeom = VTDdbf['geometry'] \n",
    "# vtdGeom = VTDdbf['geometry'] #can't use VTDdbf because it uses alternate coordinate system\n",
    "vtdTrump = VTDdbf['G20PRERTRU']\n",
    "vtdBiden = VTDdbf['G20PREDBID']\n",
    "\n",
    "nPrecincts = len(vtdGeom)\n",
    "stateGOP = np.sum(vtdTrump)/(np.sum(vtdTrump) + np.sum(vtdBiden) ) \n",
    "print(nPrecincts, stateGOP, np.sum(vtdTrump) + np.sum(vtdBiden),\n",
    "      \"= number of precincts, statewide GOP vote, total Trump+Biden votes\" )\n",
    "vtdTrump = vtdTrump.to_numpy()  #these two lines try to avoid pandas complaints when we overwrite precinct data\n",
    "vtdBiden = vtdBiden.to_numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c5c57f52-b8d2-4ef4-9d02-2429ed5e59da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#see NJ code for convex-hulling tracts\n",
    "#ID the non-polygon PRECINCTS\n",
    "notPolyVTD = [0]*nPrecincts\n",
    "for p in range(nPrecincts):\n",
    "    if type(vtdGeom[p]) != type(vtdGeom[0]):\n",
    "        notPolyVTD[p] = 1\n",
    "        for geom in vtdGeom[p].geoms:    \n",
    "            xs, ys = geom.exterior.xy\n",
    "            plt.plot(xs,ys)\n",
    "        #plt.text(vtdGeom[p].centroid.x, vtdGeom[p].centroid.y,p)\n",
    "    else:\n",
    "        hi = \"hi\"\n",
    "        #x,y = vtdGeom[p].exterior.xy\n",
    "        #plt.plot(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ea498c6a-d054-409e-92fb-cda921e2911f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#prep for geography triage\n",
    "#isSkippedTract = [0]*nTracts  #for California, done in prev block when we skipped two Pacific Ocean polytracts\n",
    "isSkippedPrecinct = [0]*nPrecincts  #will be used later"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5520a7c2-0560-421c-b5ef-bfd8aa9752b3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-99999]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# For potential later issues, identify and flag lakeshore low-population tracts.\n",
    "lakeTracts = [-99999]\n",
    "minTractPop = 5\n",
    "for m in range(nTracts):\n",
    "    if tractPop[m] < minTractPop:\n",
    "        x = tractGeom[m].centroid.x\n",
    "        y = tractGeom[m].centroid.y        \n",
    "        if type(tractGeom[m]) == type(tractGeom[0]):\n",
    "            x2,y2 = tractGeom[m].exterior.xy  #turn these two on to show state map\n",
    "            plt.plot(x2,y2,c=\"blue\")\n",
    "            plt.text(x+0.3,y+0.3,m)\n",
    "        else:\n",
    "            for geom in tractGeom[m].geoms:\n",
    "                x3,y3 = geom.exterior.xy\n",
    "                plt.plot(x3,y3,c=\"red\")  #red empty tracts are nonPolygon\n",
    "\n",
    "        if y > 99999 : #don't eliminate any tracts from map yet for California; plot first\n",
    "            plt.text(x, y,m, fontsize=9)\n",
    "            isSkippedTract[m] = 1\n",
    "            if lakeTracts == [-99999]:\n",
    "                lakeTracts = [m]\n",
    "            else:\n",
    "                lakeTracts.append(m)\n",
    "                \n",
    "print(lakeTracts)  # assigned as skipped tracts as well\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "bffa3aff-9e40-405e-96aa-f1197a683a0c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#DECISION FOR CA - leave the polygon ocean-shore tracts in the map, but skip the remaining non-polygons\n",
    "#will trim offshore later with clipPoly's and healPoly's\n",
    "isSkippedTract[59] = 1\n",
    "isSkippedTract[60] = 1\n",
    "isSkippedTract[7624] = 1\n",
    "isSkippedTract[7320] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "dca817fc-8a1a-4037-bb00-3f0e2e871491",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "looking for tracts with zero area\n"
     ]
    }
   ],
   "source": [
    "# For potential later issues, identify and visualize zero-Area tracts.  See Ohio code for more code\n",
    "print(\"looking for tracts with zero area\")\n",
    "for m in range(nTracts):\n",
    "    if(tractArea[m] == 0):       \n",
    "        x = tractGeom[m].centroid.x\n",
    "        y = tractGeom[m].centroid.y\n",
    "        print( m,tractPop[m],\"(\",x,\",\",y,\")\" )\n",
    "        x2,y2 = tractGeom[m].exterior.xy\n",
    "        plt.plot(x2,y2,c=\"purple\")\n",
    "        #print(tractGeom[m])\n",
    "        plt.scatter(x, y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "3ded1b1f-5629-4d8f-826b-e037e5dcb3da",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on tract 400\n",
      "working on tract 800\n",
      "working on tract 1200\n",
      "working on tract 1600\n",
      "working on tract 2000\n",
      "working on tract 2400\n",
      "working on tract 2800\n",
      "working on tract 3200\n",
      "working on tract 3600\n",
      "working on tract 4000\n",
      "working on tract 4400\n",
      "working on tract 4800\n",
      "working on tract 5200\n",
      "working on tract 5600\n",
      "working on tract 6000\n",
      "working on tract 6400\n",
      "working on tract 6800\n",
      "working on tract 7200\n",
      "working on tract 7600\n",
      "working on tract 8000\n",
      "working on tract 8400\n",
      "working on tract 8800\n",
      "built the whole CA map, excluding a few ocean multiPolygons\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#build basic CA map\n",
    "#tractMAP = tractGeom[0] #uncomment for first time thru loop  **************\n",
    "for t in range(1,nTracts):\n",
    "    if t%400 == 0:\n",
    "        print(\"working on tract\",t)\n",
    "    if isSkippedTract[t] == 0:\n",
    "        uncomment = \"if-redone\"\n",
    "        #tractMAP = tractMAP.union(tractGeom[t])  #uncomment to build map  ********\n",
    "print(\"built the whole\",STATE,\"map, excluding a few ocean multiPolygons\")\n",
    "counter = 0\n",
    "for geom in tractMAP.geoms:\n",
    "    x,y = geom.exterior.xy\n",
    "    plt.plot(x,y)\n",
    "    plt.text(geom.centroid.x,geom.centroid.y,round(geom.area,1)+0.001*counter)\n",
    "    counter +=1\n",
    "pt1 = Point(-121,33)\n",
    "pt2 = Point(-119.3,33)\n",
    "pt3 = Point(-119.3,34.26)\n",
    "pt4 = Point(-121,34.)\n",
    "clipPoly = Polygon([pt1,pt2,pt3,pt4])  #LEFTOVER FROM INDIANA. plan to clip off SW corner near Evansville\n",
    "xc,yc = clipPoly.exterior.xy\n",
    "plt.plot(xc,yc)\n",
    "\n",
    "plt.show()\n",
    "wholeMAP = tractMAP  #in case we later slice parts out\n",
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "8e7c2c16-d377-452c-96b0-d72d4a69c6a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#OK, let's go through these one at a time\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "f33de347-5473-4b11-b3ae-86691b33098d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I have flagged  4 tracts w pop 2177.0  to reassign to tracts...\n",
      "[183, 1880, 1881]\n",
      "I have flagged  2 precincts to reassign to precincts...\n",
      "[20179, 20200, 20204, 20224, 20275, 20343, 20355, 20368, 20559]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#find all tracts and precincts centered in this clipPoly, flag for cutting\n",
    "# and, ID all nearby tracts and precincts to receive their pops and voters\n",
    "cutTractList = [-99999]\n",
    "cutPrecinctList = [-99999]\n",
    "tractReceivers = [-88888]\n",
    "precinctReceivers = [-88888]\n",
    "popToCut = 0.\n",
    "for t in range(nTracts):\n",
    "    x = tractGeom[t].centroid.x\n",
    "    y = tractGeom[t].centroid.y\n",
    "    if tractGeom[t].intersects(clipPoly) :\n",
    "        CP = Point(x,y)\n",
    "        if CP.intersects(clipPoly):\n",
    "            isSkippedTract[t] = 1\n",
    "            popToCut += tractPop[t]\n",
    "            if cutTractList == [-99999]:\n",
    "                cutTractList = [t]\n",
    "            else:\n",
    "                cutTractList.append(t)\n",
    "            if notPoly[t] == 0:\n",
    "                x,y = tractGeom[t].exterior.xy\n",
    "                plt.plot(x,y)\n",
    "            else:\n",
    "                for geom in tractGeom[t].geoms :\n",
    "                    x,y = geom.exterior.xy\n",
    "                    plt.plot(x,y)\n",
    "    else:\n",
    "        if tractGeom[t].distance(clipPoly) < 0.02 : #and tractGeom[t].centroid.x > -76.4:\n",
    "            if tractReceivers == [-88888]:\n",
    "                tractReceivers = [t]\n",
    "            else:\n",
    "                tractReceivers.append(t)\n",
    "xp,yp = clipPoly.exterior.xy\n",
    "plt.plot(xp,yp)\n",
    "\n",
    "for p in range(nPrecincts):\n",
    "    x = vtdGeom[p].centroid.x\n",
    "    y = vtdGeom[p].centroid.y\n",
    "    if vtdGeom[p].intersects(clipPoly) :\n",
    "        CP = Point(x,y)\n",
    "        if CP.intersects(clipPoly):\n",
    "            isSkippedPrecinct[p] = 1\n",
    "            if cutPrecinctList == [-99999]:\n",
    "                cutPrecinctList = [p]\n",
    "            else:\n",
    "                cutPrecinctList.append(p)\n",
    "    else:\n",
    "        if vtdGeom[p].distance(clipPoly) < 0.02 :# and vtdGeom[p].centroid.x > -76.4 :\n",
    "            if precinctReceivers == [-88888]:\n",
    "                precinctReceivers = [p]\n",
    "            else:\n",
    "                precinctReceivers.append(p)\n",
    "print(\"I have flagged \",len(cutTractList),\"tracts w pop\",popToCut,\" to reassign to tracts...\")\n",
    "print(tractReceivers)\n",
    "print(\"I have flagged \",len(cutPrecinctList),\"precincts to reassign to precincts...\")\n",
    "print(precinctReceivers)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "33897c0d-3254-4a76-9b82-314a8f320eaa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#clipPoly block 2 of 4\n",
    "#visualize the to-be-cut precincts, just to confirm there are really xx precincts up there\n",
    "for p in range(nPrecincts):\n",
    "    if isSkippedPrecinct[p] ==1:\n",
    "        if notPolyVTD[p]==1:\n",
    "            for geom in vtdGeom[p].geoms:\n",
    "                x,y = geom.exterior.xy\n",
    "                plt.plot(x,y)\n",
    "        else:\n",
    "            x,y = vtdGeom[p].exterior.xy\n",
    "            plt.plot(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "e2595c62-579a-4af1-9552-0859524782be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#clipPoly block 3 of 4\n",
    "#now visualize the receivers\n",
    "for pp in range(len(precinctReceivers)):\n",
    "    p = precinctReceivers[pp]\n",
    "    if notPolyVTD[p]==1:\n",
    "        for geom in vtdGeom[p].geoms:\n",
    "            x,y = geom.exterior.xy\n",
    "            plt.plot(x,y)\n",
    "    else:\n",
    "        x,y = vtdGeom[p].exterior.xy\n",
    "        plt.plot(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "9e1d7fcd-cdeb-4317-9f89-5291a9595587",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#now visualize the TRACT receivers\n",
    "for tt in range(len(tractReceivers)):\n",
    "    t = tractReceivers[tt]\n",
    "    if notPoly[t]==1:\n",
    "        for geom in tractGeom[t].geoms:\n",
    "            x,y = geom.exterior.xy\n",
    "            plt.plot(x,y)\n",
    "    else:\n",
    "        x,y = tractGeom[t].exterior.xy\n",
    "        plt.plot(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "d2622568-1fc9-4089-9ae4-2550ea6fbaaf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I have finished slicing  2177.0 people (VAP of 1886.0 ) and  2.0 voters out.\n"
     ]
    }
   ],
   "source": [
    "#now, cut and redistribute\n",
    "cutPop = 0.\n",
    "cutVAP = 0.\n",
    "cutHisp = 0.\n",
    "cutBlack = 0.\n",
    "cutTrump = 0.\n",
    "cutBiden = 0.\n",
    "\n",
    "for ct in range(len(cutTractList)):\n",
    "    t = cutTractList[ct]\n",
    "    cutPop += tractPop[t]  #sum up the cut pops\n",
    "    cutVAP += tractVAP[t]\n",
    "    cutHisp += tractHisp[t]\n",
    "    cutBlack += tractBlack[t]\n",
    "    # Now we zero out the pops in the cut tracts\n",
    "    tractPop[t] = 0\n",
    "    tractVAP[t] = 0\n",
    "    tractHisp[t] = 0\n",
    "    tractBlack[t] = 0\n",
    "# Now distribute the pops among the receivers\n",
    "ntR = len(tractReceivers)\n",
    "NTR = float(ntR)\n",
    "for rt in range(ntR) :\n",
    "    t = tractReceivers[rt]\n",
    "    tractPop[t] += cutPop/NTR\n",
    "    tractVAP[t] += cutVAP/NTR\n",
    "    tractHisp[t] += cutHisp/NTR\n",
    "    tractBlack[t] += cutBlack/NTR\n",
    "\n",
    "#             now do the same for the precincts\n",
    "for cp in range(len(cutPrecinctList)):\n",
    "    p = cutPrecinctList[cp]\n",
    "    cutTrump += vtdTrump[p]\n",
    "    cutBiden += vtdBiden[p]\n",
    "        # Now we zero out the pops in the cut precincts\n",
    "    vtdTrump[p] = 0\n",
    "    vtdBiden[p] = 0\n",
    "\n",
    "# Now distribute the pops among the receivers\n",
    "npR = len(precinctReceivers)\n",
    "NPR = float(npR)\n",
    "for rp in range(npR) :\n",
    "    p = precinctReceivers[rp]\n",
    "    vtdTrump[p] += cutTrump/NPR\n",
    "    vtdBiden[p] += cutBiden/NPR\n",
    "print(\"I have finished slicing \",cutPop,\"people (VAP of\",cutVAP,\") and \",cutBiden+cutTrump,\"voters out.\" )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "fe47f683-719d-4a02-9648-905bddbf28a3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Now, repeat for southeast island\n",
    "\n",
    "counter = 0\n",
    "for geom in tractMAP.geoms:\n",
    "    x,y = geom.exterior.xy\n",
    "    plt.plot(x,y)\n",
    "    plt.text(geom.centroid.x,geom.centroid.y,round(geom.area,1)+0.001*counter)\n",
    "    counter +=1\n",
    "\n",
    "pt1 = Point(-119,32.5)\n",
    "pt2 = Point(-118,32.5)\n",
    "pt3 = Point(-118,33.4)\n",
    "pt4 = Point(-118.7,33.9)\n",
    "clipPoly = Polygon([pt1,pt2,pt3,pt4])  #LEFTOVER FROM INDIANA. plan to clip off SW corner near Evansville\n",
    "xc,yc = clipPoly.exterior.xy\n",
    "plt.plot(xc,yc)\n",
    "\n",
    "\n",
    "plt.show()  #note that for CA, the 0th polygon is our \"keeper\", the others we will eliminate from map later"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "cac3531a-35c7-438d-b5b9-5fcdf0745329",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I have flagged  2 tracts w pop 3875.0  to reassign to tracts...\n",
      "[2502, 2845, 2846, 3601, 3603]\n",
      "I have flagged  3 precincts to reassign to precincts...\n",
      "[4438, 5986]\n"
     ]
    },
    {
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2OCaERUgEIzuPZGTnkdw3+j7WFq8lK98pBrd853KiI6I5t9u5zhlAz4m0i2nndshhyR6XGOIe+/oxXl7/MouuXES3Nt3cDseEoRqtIac4h8X5i1lSsIS9x/YSFRHF2G7OGcD5KedbB+ADfhvTbwmW9H2jpLyEKfOncEHKBfx+3O/dDscYarSGb/Z/Q1a+cxXQ7rLdzmWiXc9hSuoUJqVMsjPSZrKkb3g652n+uvqvzL90vtXZMQFHVb/TARSVFRElUZzd7Wympk61DqCJLOmHuRNVJ5i6YCqDOg3i75P/7nY4xvwgVSXvQF7dHEBhaaHTAXQ9mympztmqPeznh1nSD3OvbXyNR758hOcynmN019Fuh+M9VTi6B0p2wpFCKC2GYwegsgyqK6GmCmqqQQQQkAjne4lwXojn/cnLGlovAgTna2QMxLSBuE7Qtisk9IQ2nT37MS1JVVl3YJ3zRLD8LHaV7iJSIhndZTQZaRlckHIBHVp3cDvMgGNJP4xV11Rz2VuX0S6mHS9f/HLgFlZThYPbYNfXULQG9uTA3lw4UXLSigLRsRARDRGRzgtAa5zP0BpAv/3+O8tqvr/MW9Hx0KkPdOoLif2cr7XvW9uwQ0tQVdYfXF93BrDz6E4ixblMNCM1g8mpk+nYuqPbYQYES/phLCs/i59/9HP+POHPZKRluB3O9x07CNlzYfWLcGCLsyw6DjoPhs5DIDkdOqRBu27O0XZsB4j0YRXwkzsHrYHqCqgohbL9cHQ3HN4BB7Y68R3YAocLPJ2GR3zyt51AXYfQ14k7yh5K4g+qyoaDG1hSsISsgiwKjhQQIRGc1fmsujOATrGd3A7TNZb0w5SqcsN7N1BSUcK7l78bWHV2SnbBJ3+GNa9A1XFIGQtDroTUsZA08Nsj+EBUVQ6H8p0OYP9mT2fg6RTK9n27nkRAQip0HQpdh0G3Ec4r1oYjfElV2XRoU91loPlH8uvuE6g9A0iMTXQ7zBZlST9Mfb3na25bfBu/HvNrrh1wrdvhOGpq4MvHYdl/OUfXQ6+Fs++ALkNOvW0wOH4YDm79thMo3gC7c+DQ9m/X6dDr2w6g2winQ2ht16b7Qm0HUHsGsL1kO4I4HUBaBpNTJpMUl+R2mH5nST9M3bn0TtYdWBc4hdWqK2H+bbD+HRhwMVz4B0hIcTuqlnH8EOxeC0WroTDbmbco2eH5oTjDQvU7gi5DIcYqVZ4OVWXL4S11k8DbSrYhCCOSR5CRlsGU1CkkxyW7HaZfWNIPQxsPbuTqd6/m7hF3c/vQ290Ox7Hst/DxY5DxWzjnX+1qmLL9TvIvWg1F2c7Xo7udn0kEJA3ydALDofuZzhyHzRE029bDW+smgbcc3vKdDmByymQ6x3d2O0SfsaQfhh745AE+2PEBS65eEjg3tfyxH/Q4C65/2e1IAteR3bB7jedswNMZHDvg/CwiGjqn1zsjOBOSB0FktKshB6Nth7exuGAxWflOBwAwPGl43RlAl/guLkd4eizph5mi0iIueuMirh94PfeNvs/tcBzVVfBIJ5j4S5gYIDEFA1Vn0rv2TKD2VXspa2Qr6HKG0wl0P9P5mtg/sCfCA8y2km0syXfmADYd2gTAsKRhZKRmkJGWEZQdgCX9MPPoV48yb8M8Fl25iK5turodjuNECfwhxRnaGftjt6MJbrX3NNR1Amucs4MKz5NMo+PqXS3k6Qg69bHhNC/kl+TXzQFsPLQRgKGJQ+vOAIKlUKEl/TBSW1htcspkfjfud26H862SQvjvdLj0f2HkrW5HE3pqauDA5u+eDezOcS6HBWjbDfpNgf5TofdEiLGnWZ1KwZEC5yqg/CzWH1wPwBmJZ5CRmsGUtCl0b9Pd5QgbZ0k/jDy19in+tuZvLLhsAf079Hc7nG8Vb4LHz4KrnoMzrnY7mvBQXeVcMlq4ErYugy3LoOKoMySUdp7TAfTLgI693I404O04sqPuDKC2AxjcaTAZaRlkpGbQo20PlyP8Lkv6YaK2sFp6p3SenPyk2+F8V+EqeGYSXP8qDJjmdjThqaoCdnwBmxbD5sXf3gGdOAAGXQJDrnLuhDY/aOfRnXVnAHkH8gBI75ReNwfQs21PlyO0pB82agurzZ46m7O6nOV2ON+1/WOYeyncshB6jXM7GgPODWSbFsOm9yH/U9BqSB4Mo/8Zhl5n9wl4YdfRXXUdQO6BXAAGdRxUdwaQ0s6d+1As6YeB6ppqLn3rUhJaJfDSRS8FXmG1DYtg3vVw+3JnYtEEltJiWPcWZD/vFLuL7QBj7nLup7Dxf68UlRbVdQA5+3MAGNhxoDMHkDqFtPZpLRaLJf0wsDh/Mb/46Bf8ZeJfmJI6xe1wvi/ndXjjR/Djlc7dpyYwqTpDQJ//FTYugjZd4PxfwoiZdhloE+wu3e3MARRkkVPsdAD9O/SvGwLq1d6/8yiW9EOcqjLjvRmUVZbx9vS3A6uwWq2VmbDwJ/Cz9U7FTBP4dnwJWb9yyl0nDYIp/+lcARRoZ5EBbk/ZnrozgDXFawDo16Gf0wGkZtA7obfP9+lt0o/w4oNai8hXIrJWRPJE5Dee5Y+ISI6IrBGRLBFp9H+1iESKyGoRWdi0ZpjGfL3na9YdWMctg28JzIQP315DHtPG3TiM91LGwD8tgWvmQtUJePkaeH66U0PIeK1LfBduSr+JFy56gSVXL+G+s+6jbXRbnljzBNPfns4Vb1/Bk2ueZOvhrS0e2ymP9MUZKI5X1VIRiQY+Be4F1qnqEc869wDpqnpHI5/xM2AU0E5VLzlVUHakf2p3LLnDebjE1Vm0igzQ2izL/wDLfw8PHbRhgmBUVQErZ8NHjzrF44ZeB5N+5TxVzDTLvmP76s4AVu9bjaL0ad+n7kawvgl9mz0357MjfXV4DtmI9ry0NuF7xNPII4lEpAdwMfDsKaM2Xtl4cCOfFX3GzEEzAzfhA5Qfde4UtYQfnKJiYMwdcM9qOPceyHsT/joSlv5HA083M95IjkvmxkE3MvfCuSy9ZikPjH6ADq078Pe1f+fKd67knmX3+D2GUyZ9qBueWQPsA5ao6grP8t+KyE7gRuChRjb/H+DfgZpGfl67j9tFZKWIrCwuLvYy/PCUmZdJXFRc4NTLb0xFmV0FEgpiE5yx/btXwuDL4dP/hv8bASuecs4GTLMkxyVzw6AbyJyWybJrlzG221i+2f+N3/frVdJX1WpVHQ70AEaLyBDP8gdVtSfwEvC94ioicgmwT1VXebGPp1V1lKqOSkoK/QceNFdRaRHvb3+fq/tfHTiVNBtTUWbj+aEkIQWufBpu/8i5oesf/w5PnA3r3nauADLNlhib2GIlHrxK+rVU9TCwHDj59sqXgasa2ORc4DIRyQfmAZNE5MUmR2nqPL/ueQThpvSb3A7l1CpKLemHom7D4eZ34IbXnfIOr90Ms6fCzq/cjsx4wZurd5JEJMHzfSwwGdggIvUvvL4M2HDytqr6gKr2UNU0YAawTFVn+iLwcHT4xGHe2PwGF/W+KDhKv1aU2vBOqBKB/hlwx6dw6f85zw9+borTARwqcDs68wO8OdLvCnwoIjnA1zhj+guBP4hIrmd5Bs4VPYhINxFZ5LeIw9i8jfM4XnWcWwff6nYo3ikvhVZ2pB/SIqNg5C1wdzZMfAA2L4HHR8OXT9qQT4CKOtUKqpoDfO8eelVtaDgHVS0CLmpg+XKcoSHTDCeqTvDy+pcZ32M8/ToEyd2tFWV2eV8AenP1Ln766lq6J8Ty60sGMXFAMq2jT/MKq1ZtYOL9MOImeO/n8P79TsG9S//P6vkEmFMmfRMY3tryFofKDzFr8Cy3Q/FeRSnEtHU7ClPPgdJyfvqqc6NV4eHj3PFiNvExkUxJ78wlQ7sxrn8iraJOowNo3x1mvAyf/gWW/ZdzaeeMl+3xjgHEkn4QqKqpYm7eXIYmDmVk55Fuh+M9G9MPGIePVXD9MytYv9u5vWba4C78PKM/e4+UszCniPmrdvHWmiIAPvzFRHolnsbvLSICxv8C4jo5ZTjevRemP26lHAJEk67eMe5YumMpu0p3cduQ2wKvkmZjVJ3hHRvTDwivfLWzLuEDlByv5M3VhVTW1NA+LpqYKCcVdE+IpUOcj47KR81yxvnXvOS8TECwI/0Ap6pk5maS1i6NiT0nuh2O96rKoabKjvQDxK1j04iNjqBXUhs+WL+X1TsO88TyrbB8K5ERQkZ6Z+6c2IehPRJ8u+MJ98HmLPjwd84DW6Jjffv5psks6Qe4FXtWsO7AOh4+5+HALazWkIoy56tdpx8QYmMiufVcp7TvhP7OzY+HyipYs+swA7u0pWt7PyVjEZj8H87DdHJetWclBwBL+gEuMzeTTq07cWmfS90OpWkqjjpfLekHrA7xMZw/INn/O0obBwiUFPp/X+aUbEw/gG04uIHPiz5nZnqAF1ZrSN2Rvg3vhL0TJYBCdGu3IzFY0g9omblBUlitIeWewqw2kWuKVjtf7ZGZAcGSfoAqLC1kcf5irul/De1i2rkdTtPZA1RMrUJPvUVL+gHBkn6Aej7veUSEmelBWqrIhndMraLV0LGP8+B14zpL+gHo0IlDvLH5DS7udXFwFFZriB3pm1qF2dD9TLejMB6W9APQvI3zOFF9IngKqzXELtk0AEf3wNEi6GZJP1BY0g8wx6uO88r6V5jQYwJ9O/R1O5zmK/dcsmkTueGtMNv5akf6AcOSfoCpK6w2JIgKqzWkogwkAqLsMr2wVrgKJBK6DHU7EuNhST+A1BZWG5Y0jDOTg/zIqKLMqbAZLLWCjH8UZUNyupVXDiCW9API0oKlFJYWMmvIrOAprNaYiqN25U64U3Wu3Olul2oGEkv6AUJVmZ07m7R2aZzf83y3wzl9FWWW9MPdoe1w/JBN4gYYS/oB4svdX7L+4HpuHXwrERICvxZ7VKKxSdyAFALZJTRk5maSGJsYfIXVGlNRZpdrhrvCbGciPznd7UhMPadM+iLSWkS+EpG1IpInIr/xLH9ERHJEZI2IZIlItwa27SkiH4rIes+29/qjEcFu3YF1fLH7C2YOmklMZIzb4fhGxVFL+uGuKNu5ascelRhQvDnSLwcmqeowYDgwTUTGAH9U1aGqOhxYCDzUwLZVwM9VdRAwBvhXEbFu/yRzcucQHx3PNQOucTsU37Ex/fBWXQW719rQTgA6ZdJXh+eeeqI9L1XVI/VWiwe0gW13q2q25/ujwHqg+2lHHUJ2Hd3F4oIgLqzWGHtUYnjbvxEqj9kkbgDy6iEqIhIJrAL6Ao+r6grP8t8CNwMlwA9eciIiacAIYEUjP78duB0gJSXFu+hDwPPrnidCIpg5KEgLqzWmvNSGd8KZTeIGLK8mclW12jOM0wMYLSJDPMsfVNWewEvAjxvbXkTaAAuAn5x0hlB/H0+r6ihVHZWUlNTEZgSngycO8ubmN7mk9yV0ju/sdji+U1MDlTa8E9aKsqFVO6e6pgkoTbp6R1UPA8uBaSf96GXgqoa2EZFonIT/kqq+0fQQQ9e8DSFQWK0hlVZsLewVrnLq50fYBYKBxpurd5JEJMHzfSwwGdggIv3qrXYZsKGBbQV4Dlivqn/xScQh4ljlMV7Z8AoTe0ykT0KIHQ1ZLf3wVnkC9ubZ0E6A8mZMvysw1zOuHwG8pqoLRWSBiAwAaoAC4A4Az6Wbz6rqRcC5wE3ANyKyxvN5v1TVRT5uR9B5a8tbHC4/zG1n3OZ2KL5X96jEtu7GYdyxNxdqqmwSN0CdMumrag7OBOzJyxsczlHVIuAiz/efAkFeRMb3qmqqeH7d8wxPGs6I5BCsS1L3ABU70g9LNokb0GzAzQVZ+Vl1hdVCkj1AJbwVZUN8MrSzq7MDkSX9FqaqZOZl0qt9Lyb2nOh2OP5hj0oMb4WroPtIK6sdoCzpt7Avdn/BhoMbmDV4VmgUVmuIDe+ErxNHYP9mG9oJYCGadQLX7NzZJMUmcXHvi90OxX/qJnLtSD/s7F4DqE3iBjBL+i0o70AeK3avYGZ6CBVWa4hdshm+aidxu4XgBQohwpJ+C5qTO4c20W24pn8IFVZriE3khq+ibEhIhfhObkdiGmFJv4XsPLqTrIIsrhlwDW1jQvz69YqjENnKSuqGo8JsZxLXBCxL+i1kbt7c0Cys1hArqxyeSouhZKdN4gY4S/ot4OCJg7y15S0u7X0pyXHJbofjf/aoxPBUVDueb0k/kFnSbwGvbHiF8ury0Cus1pgKK6sclgqzQSKg6zC3IzE/wJK+n9UWVju/5/n0Tujtdjgtw5J+eCrKhsQBdpYX4Czp+9mbW96kpLyE24aEYGG1xtiYfvhR/fZOXBPQLOn7UWVNJXPz5jIieQTDk4e7HU7LsUclhp/DO+DYAehu1+cHOkv6fpSVn8Xust3MGhyihdUaY49KDD82iRs0LOn7iaqSmZtJ7/a9mdBzgtvhtKyKUhveCTeF2RAZA52HuB2JOQVL+n7yedHnbDy0kVsH3xq6hdUaYxO54adotZPwo0K4vEiICLNs1HIyczNJjk0O7cJqDamqgOoKS/rhpKbaSfo2iRsULOn7Qd7+PFbsCYPCag2psAqbYWf/Zuf3bnfiBgVL+n6QmZcZHoXVGlJT5XytTf4m9NkkblA5ZdIXkdYi8pWIrBWRPBH5jWf5IyKSIyJrRCTL80D0hrafJiIbRWSLiNzv6wYEmp1HdrKkYAnXDriWNuE4xBGfBKnnwVfPfFtX34S2wmxnOC+xn9uRGC94c6RfDkxS1WHAcGCaiIwB/qiqQ1V1OLAQeOjkDUUkEngcuBBIB64XkXQfxR6Q5q6bS6REhkdhtYaIwOSHoXQfvHuvc9OOCW1F2dB1OEREuh2J8cIpk746ag/Zoj0vVdUj9VaLBxr63z0a2KKq21S1ApgHTD/NmAPWgeMHeGvLW1zW5zKS4pLcDsc9PUfDBb+G3Pnw0aOW+ENZVQXs+cbG84OIV2P6IhIpImuAfcASVV3hWf5bEdkJ3EgDR/pAd2Bnvfe7PMsa2sftIrJSRFYWFxc3oQmB45UNr1BRXcEtg29xOxT3nfczGDoDlv8eXp0JZfvdjsj4w95c52otS/pBw6ukr6rVnmGcHsBoERniWf6gqvYEXgJ+3MCm0tDHNbKPp1V1lKqOSkoKvqPk+oXVerXv5XY47hOBy5+EjP+CzVnwxBjY+L7bURlfs0ncoNOkq3dU9TCwHJh20o9eBq5qYJNdQM9673sARU3ZZ7B4Y/MbHKk4wqwhYVZy4YdERMDYu+H25dCmC7xyHbxzj03whpLC1RDXCRJS3I7EeMmbq3eSRCTB830sMBnYICL1p+ovAzY0sPnXQD8R6SUiMcAM4J3TjjrAVNZU8vy65zkz+czwKqzmrc6D4Z8/gHN/AtnPw9/Pgx0r3I7K+EJRtnOULw2d1JtA5M2RflfgQxHJwUniS1R1IfAHEcn1LM8A7gUQkW4isghAVatwhn0WA+uB11Q1zw/tcNXi/MXsLtsdXuWTmyqqFUz5DcxaBFoNmdPgg/90JgJNcCovheINdidukIk61QqqmgN8r16qqjY0nIOqFgEX1Xu/CFh0GjEGtNrCan3a92Fcj3FuhxP4UsfCnZ/D+w/AJ3+GzUvgymcgeaDbkZmm2r0WtMYmcYOM3ZF7mj4r+oxNhzZx65AwLKzWXK3awvS/wYyX4UgRPDUevngCamrcjsw0hU3iBiXLUqcpMzeT5LhkLu4VZoXVfGHgxXDXl9D3Alj8ALwwHUp2uR2V8VZhNrTvCW2C72q7cGZJ/zTk7s/lqz1fcXP6zURHRrsdTnBqk+Qc8V/2V9i1Cp4YCzmv2Q1dwaAoG7rZk7KCjSX90zA7dzZto9tyVb8GpzeMt0TgzJvhzk+dsf03/hnmz4JjB92OzDTm2EE4lG+TuEHIkn4z7Tiyg6UFS8O3sJo/dOwNs/4BFzwM6xfCE+fAlqVuR2UaUugZz7dJ3KBjSb+Z5ubNJSoiipnpYVpYzV8iImHcz5zr+mMT4MWr4L1fQMUxtyMz9RVlA+IUWjNBxZJ+M+w/vr+usFpibKLb4YSmrsPg9o/gnB/D18/AU+OgcJXbUZlahdlOKeXW7dyOxDSRJf1meHn9y1TWVFphNX+Lbg1Tfwu3vAuVJ+DZKbD8D1Bd6XZk4U312ztxTdCxpN9ExyqPMW/jPCalTLLCai2l13i48zM44xqnaufsqbB/i9tRha8jRVC618bzg5Ql/SZasHkBRyuOWsmFlhabAFc+BdfMhYPbnPo9XzzuPJTbtKzaYTa7cicoWdJvgtrCaiM7j2Ro0lC3wwlPgy93bujqPQEW/9I56i/e6HZU4aUoGyKioPMQtyMxzWBJvwne3/4+e8r22FG+29p2gevnwZXPwoGtzlH/x3+ysf6WUpjtVE6Nbu12JKYZLOl7SVWZnTubvgl9Oa/7eW6HY0Rg6DXwr1855RyWPQLPnO8UATP+U1MDRWtsEjeIWdL30qeFn7Ll8BZmDZllhdUCSZskuGYOXPei8zD2p893SjZXnnA7stB0cBuUl9gkbhCz7OWl2bmz6RzXmQvTLnQ7FNOQQZfCv66AYTOcks1PjYedX7sdVeixSdygZ0nfCznFOazcu5Kb0m+ywmqBLLYDXP4E3LgAKsrguSlO3f6KMrcjCx1F2RAdB4kD3I7ENJMlfS/MyZtD25i2XN3/ardDMd7oNxnu+gJG3QZfPgFPjoXtH7sdVWgozHbulo485fOXTICypH8KBUcKWFqwlBkDZhAfHe92OMZbrdvBJX+BW98DBOZeCu/eCydK3I4seFVXwp4cm8QNcpb0T2FO3hyiI6K5YdANbodimiPtPOfxjOf82Hko+9/OgjUv21O6mmPfeqg6YZO4Qe6USV9EWovIVyKyVkTyROQ3nuV/FJENIpIjIm+KSEIj2//Us12uiLwiIkFzce/+4/t5Z8s7XNbXCqsFtZg4p4bPj5ZC+x7w1p3w+Gj4+lkoP+p2dMGjbhLXkn4w8+ZIvxyYpKrDgOHANBEZAywBhqjqUGAT8MDJG4pId+AeYJSqDgEigRk+it3v6gqrpVthtZDQfST801K4OhNi4uG9n8OfBsDrs2DdO1B53O0IA5cqbHof4pOgg9WcCmannI1RVQVKPW+jPS9V1ax6q30JNDbLGQXEikglEAcUNT/cllNWWca8jfOYnDqZtPZpbodjfCUiAoZcCYOvcI5cV78I69+FvDcgOh4GTIP0y6HfFIiOdTvawFBTA0sfdpL+pF85N8aZoOXVFLyIRAKrgL7A46q64qRVbgNePXk7VS0UkT8BO4DjQNZJnUXAmr9pPkcrjnLr4FvdDsX4gwj0GOW8LvoTFHwKeW/B+ncgd4F1ALVK98G7P4GN78Gof4Jxv3A7InOavEr6qloNDPeM278pIkNUNRdARB4EqoCXTt5ORDoA04FewGHgdRGZqaovNrDu7cDtACkpKc1qjK9UVlfywroXGNV5lBVWCweRUdB7ovOyDsBxeAesfsmpZFpdDlN/D2PutKP8ENCki21V9bCILAemAbkicgtwCXCBZxjoZJOB7apaDCAibwBjge8lfVV9GngaYNSoUQ19Vov5R/4/2HtsLw+d85CbYRg3NNgBvOkMAYV6B3DsIGxcBGvnQf4nzrL+F0LGI85TskxIOGXSF5EkoNKT8GNxEvmjIjINuA+YoKqNPcB0BzBGROJwhncuAFb6JnT/UFUyczPpm9CXcd3HuR2OcdN3OoA/h1YHoApHCmHfBtj7DWz5AHZ8ATVVzkTt+b+CYddBgrtn3cb3vDnS7wrM9YzrRwCvqepCEdkCtAKWiHPK96Wq3iEi3YBnVfUiVV0hIvOBbJwhoNV4juYD1SeFn7Dl8BZ+d97vEDuVNbWCrQOoqYGyYiexH93tPO2qZBcc2g4HtjmF0yrrlafoPATG3gPplzkPO7e//ZDlzdU7OcCIBpb3bWT9IuCieu8fBh4+jRhb1Ozc2XSJ78K0XtPcDsUEqpM7gPxPYN1b3+0A+l4AaeOgx0jofAZExfhu/1UVTiI/uttJ6keK4Mju7yb4o7udo/b6IqIgIRU69YVe46BTH0gaBMmDIK6j7+IzAc0KaNSztngtq/au4t9G/RvREVZYzXghMgr6nO+86jqAt2HTYmciGCCylZNYO/V1Em2nvk6SjYiC9j2/e1RdUw3HD8PxQ86Rev0kfqTQSe5l+74fR3QctOvmvFLP/fb7uld3iEt0Llk1Yc2Sfj1zcufQLqadFVYzzVO/A1B1hlMKV8KulU4Jg11fO2cCNPE6hdgOTtJu29UZemnXHdp1dZJ5W09Sb93ehmSMVyzpe2wv2c4HOz7gR2f8iLjoOLfDMcFOBBJ6Oq/BV3y7vKocDm53rpLZugyG3/jdZC2RTgKP7QDxidCms1NGwhgfsaTvMTdvrhVWM/4X1QqSBzqvcT9zOxoThmyAD09hta3vML3vdCusZowJaZb0gZfWv0RVTZWVXDDGhLywT/qlFaW8uuFVJqdOJqWd3YhijAltYZ/0F2xewNHKo9w25Da3QzHGGL8L66RfWV3J8+ue56wuZzEkcYjb4RhjjN+FddJftH0R+47ts6N8Y0zYCNukX6M1ZOZm0q9DP87tdq7b4RhjTIsI26T/ya5P2FqylVmDZ1lhNWNM2AjbpD87dzZd47taYTVjTFgJy6S/Zt8asvdlc3P6zVZYzRgTVsIy6WfmZtIuph1X9rvS7VCMMaZFhV3S31ayjQ93fsiMgTOssJoxJuyEXdJ/Pu95YiJjuGGgFVYzxoSfsEr6xceKeWfrO1ze93I6xXZyOxxjjGlxYZX0X1z/ItVazc3pN7sdijHGuCJskn5pRSmvbXyNySlWWM0YE75OmfRFpLWIfCUia0UkT0R+41n+RxHZICI5IvKmiCQ0sn2CiMz3rLteRM7xcRu8Mn/TfEorS63kgjEmrHlzpF8OTFLVYcBwYJqIjAGWAENUdSiwCXigke3/F3hfVQcCw4D1px11E1VWV/LCuhc4u8vZDE4c3NK7N8aYgHHKpK+OUs/baM9LVTVLVas8y78Eepy8rYi0A8YDz3k+q0JVD/si8KZYuG0h+47vY9aQWS29a2OMCShejemLSKSIrAH2AUtUdcVJq9wG/KOBTXsDxUCmiKwWkWdFJL6RfdwuIitFZGVxcbH3LTiFGq1hTt4cBnQYwNhuY332ucYYE4y8SvqqWq2qw3GO5keLSF3xeRF5EKgCXmpg0yjgTOBJVR0BlAH3N7KPp1V1lKqOSkpKalorfsDHuz5mW8k2Zg2xwmrGGNOkq3c8QzPLgWkAInILcAlwo6pqA5vsAnbVOzOYj9MJtJjM3Ey6xXcjIy2jJXdrjDEByZurd5Jqr8wRkVhgMrBBRKYB9wGXqeqxhrZV1T3AThEZ4Fl0AbDOF4F7o66w2mArrGaMMeAMv5xKV2CuiETidBKvqepCEdkCtAKWeIZNvlTVO0SkG/Csql7k2f5u4CURiQG2AS02mzo7dzbtW7Xnir5XtNQujTEmoJ0y6atqDjCigeV9G1m/CLio3vs1wKjmh9g8tYXV7hh2hxVWM8YYj5C9I3du3lxaRbbi+oHXux2KMcYEjJBM+vuO7ePdre9yed/L6di6o9vhGGNMwAjJpF9bWO2Wwbe4HYoxxgSUkEv6RyuO8vrG18lIzaBn255uh2OMMQEl5JJ+bWG1W4fc6nYoxhgTcEIq6VdUVziF1bqezeBOVljNGGNOFlJJ/71t71F8vJjbBlv5ZGOMaYg3N2cFhRqt4aHPHwLg0a8fRb62OjvGmOCx7/g+YiJi/L6fkEn6x6uO133fJ6GPi5EYY0zT9U7ozfCk4X7fT8gk/fjoeL655Ru3wzDGmIAWUmP6xhhjfpglfWOMCSOW9I0xJoxY0jfGmDBiSd8YY8KIJX1jjAkjlvSNMSaMWNI3xpgwIqrqdgzfIyLFQEEzN08E9vswnGBgbQ594dZesDY3VaqqJp1qpYBM+qdDRFaqaos/k9dN1ubQF27tBWuzv9jwjjHGhBFL+sYYE0ZCMek/7XYALrA2h75way9Ym/0i5Mb0jTHGNC4Uj/SNMcY0wpK+McaEkaBI+iJyjYjkiUiNiIyqt7yTiHwoIqUi8reTtrlORHI82z32A5/9gIhsEZGNIjLVn+1oima2+XoR+cbT7vdFJLGBz40Wkbme9daLyAMt0R5v+KvNnvWGisgXns//RkRa+7s93vBnmz3rpng+4xf+bEdT+PFve4qIrPKst0pEJrVEe7zh57/tpuUwVQ34FzAIGAAsB0bVWx4PnAfcAfyt3vJOwA4gyfN+LnBBA5+bDqwFWgG9gK1ApNvtbWabo4B9QKLn/WPAfzTwuTcA8zzfxwH5QJrb7fVzm6OAHGBYvb+PkP4911t/AfA68Au329oCv+cRQDfP90OAQrfb2gJtbnIOC4ojfVVdr6obG1hepqqfAidO+lFvYJOqFnveLwWuauCjp+MkwHJV3Q5sAUb7MPRma0abxfOKFxEB2gFFDX20Z50oIBaoAI74NPhm8mObM4AcVV3r+bwDqlrt2+ibx49tRkQuB7YBeT4N+jT5q82qulpVa5fnAa1FpJVvo28eP/6em5zDgiLpN8MWYKCIpHmS2+VAzwbW6w7srPd+l2dZ0FHVSuBO4BucP4504LkGVp0PlAG7cc6G/qSqB1sqTl9qQpv7Ayoii0UkW0T+vQXD9Clv2ywi8cB9wG9aNEA/aMLvub6rgNWqWu7n8PyiCW1ucg4LmKQvIktFJLeB1/SmfpaqHsL5B3sV+ARnCKOqod02tHlT99dcvmyziETjtHkE0A1nOKOh8frRQLVnnV7Az0Wkd/Nb0eQ43WhzFM4p9I2er1eIyAXNb0WT43Sjzb8B/ltVS08r+GZyqc216w8GHgX+pZnhN4tLbW5yDotqajD+oqqTffx57wLvAojI7TiJ7mS7+O4ZQA8aOVX2Bx+3ebjnM7cCiMhrwP0NrHcD8L7nSGKfiHwGjMIZBvA7l9q8C/hIVfd71lsEnAl84MNYGuVSm88GrhbnIoYEoEZETqjq3xpY1+dcajMi0gN4E7i5dv2W4uLfdpNyWMAc6fuaiCR7vnYA7gKebWC1d4AZItJKRHoB/YCvWi5KnyoE0kWktsreFGB9A+vtACaJIx4YA2xooRh9zds2LwaGikicZ7hvArCuhWL0Na/arKrjVDVNVdOA/wF+11IJ3w+8arOIJADvAQ+o6mctF55fePu33fQc5vastpcz31fg9GjlwF5gcb2f5QMHgVLPOume5a/g/MdeB8yot/5lwH/We/8gzoz3RuBCt9t6mm2+w/OHkYNzltPp5DYDbXCu5sjz/Nv8m9tt9XebPe9netqcCzzmdltbos31Puc/CKyrd/z1t/0rnPmqNfVeyW63twX+tpuUw6wMgzHGhJGQHd4xxhjzfZb0jTEmjFjSN8aYMGJJ3xhjwoglfWOMCSOW9I0xJoxY0jfGmDDy/1qqhTIoLTLiAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#find all tracts and precincts centered in this clipPoly, flag for cutting\n",
    "# and, ID all nearby tracts and precincts to receive their pops and voters\n",
    "cutTractList = [-99999]\n",
    "cutPrecinctList = [-99999]\n",
    "tractReceivers = [-88888]\n",
    "precinctReceivers = [-88888]\n",
    "popToCut = 0.\n",
    "for t in range(nTracts):\n",
    "    x = tractGeom[t].centroid.x\n",
    "    y = tractGeom[t].centroid.y\n",
    "    if tractGeom[t].intersects(clipPoly) :\n",
    "        CP = Point(x,y)\n",
    "        if CP.intersects(clipPoly):\n",
    "            isSkippedTract[t] = 1\n",
    "            popToCut += tractPop[t]\n",
    "            if cutTractList == [-99999]:\n",
    "                cutTractList = [t]\n",
    "            else:\n",
    "                cutTractList.append(t)\n",
    "            x,y = tractGeom[t].exterior.xy\n",
    "            plt.plot(x,y)\n",
    "    else:\n",
    "        if tractGeom[t].distance(clipPoly) < 0.05:\n",
    "            if tractReceivers == [-88888]:\n",
    "                tractReceivers = [t]\n",
    "            else:\n",
    "                tractReceivers.append(t)\n",
    "xp,yp = clipPoly.exterior.xy\n",
    "plt.plot(xp,yp)\n",
    "\n",
    "for p in range(nPrecincts):\n",
    "    x = vtdGeom[p].centroid.x\n",
    "    y = vtdGeom[p].centroid.y\n",
    "    if vtdGeom[p].intersects(clipPoly) :\n",
    "        CP = Point(x,y)\n",
    "        if CP.intersects(clipPoly):\n",
    "            isSkippedPrecinct[p] = 1\n",
    "            if cutPrecinctList == [-99999]:\n",
    "                cutPrecinctList = [p]\n",
    "            else:\n",
    "                cutPrecinctList.append(p)\n",
    "    else:\n",
    "        if vtdGeom[p].distance(clipPoly) < 0.05 :\n",
    "            if precinctReceivers == [-88888]:\n",
    "                precinctReceivers = [p]\n",
    "            else:\n",
    "                precinctReceivers.append(p)\n",
    "print(\"I have flagged \",len(cutTractList),\"tracts w pop\",popToCut,\" to reassign to tracts...\")\n",
    "print(tractReceivers)\n",
    "print(\"I have flagged \",len(cutPrecinctList),\"precincts to reassign to precincts...\")\n",
    "print(precinctReceivers)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "d7009c9a-d5ff-4570-855d-1fb439afc32c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#clipPoly block 2 of 4\n",
    "#visualize the to-be-cut precincts, just to confirm there are really xx precincts up there\n",
    "for p in range(nPrecincts):\n",
    "    if isSkippedPrecinct[p] ==1:\n",
    "        if notPolyVTD[p]==1:\n",
    "            for geom in vtdGeom[p].geoms:\n",
    "                x,y = geom.exterior.xy\n",
    "                plt.plot(x,y)\n",
    "        else:\n",
    "            x,y = vtdGeom[p].exterior.xy\n",
    "            plt.plot(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "0218d8e6-7832-479f-b44f-b37c117ee40c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#clipPoly block 3 of 4\n",
    "#now visualize the receivers\n",
    "for pp in range(len(precinctReceivers)):\n",
    "    p = precinctReceivers[pp]\n",
    "    if notPolyVTD[p]==1:\n",
    "        for geom in vtdGeom[p].geoms:\n",
    "            x,y = geom.exterior.xy\n",
    "            plt.plot(x,y)\n",
    "    else:\n",
    "        x,y = vtdGeom[p].exterior.xy\n",
    "        plt.plot(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "5d698e51-7b2d-40b8-b932-d22f20f09bb0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#now visualize the TRACT receivers\n",
    "for tt in range(len(tractReceivers)):\n",
    "    t = tractReceivers[tt]\n",
    "    if notPoly[t]==1:\n",
    "        for geom in tractGeom[t].geoms:\n",
    "            x,y = geom.exterior.xy\n",
    "            plt.plot(x,y)\n",
    "    else:\n",
    "        x,y = tractGeom[t].exterior.xy\n",
    "        plt.plot(x,y)\n",
    "    plt.text(tractGeom[t].centroid.x,tractGeom[t].centroid.y,t)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "93a657e5-0cf3-4b17-8f7e-598435ed10d1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2502, 2845, 2846, 3601, 3603]\n",
      "[2845, 2846, 3601, 3603]\n"
     ]
    }
   ],
   "source": [
    "#OK, we want to eliminate 2502 from this list\n",
    "print(tractReceivers)\n",
    "tractReceivers = [2845,2846,3601,3603]\n",
    "print(tractReceivers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "c17c1582-29d1-41bc-8f56-b32ac70747ee",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I have finished slicing  3875.0 people (VAP of 3077.0 ) and  1474.0 voters out.\n"
     ]
    }
   ],
   "source": [
    "#now, cut and redistribute\n",
    "cutPop = 0.\n",
    "cutVAP = 0.\n",
    "cutHisp = 0.\n",
    "cutBlack = 0.\n",
    "cutTrump = 0.\n",
    "cutBiden = 0.\n",
    "\n",
    "for ct in range(len(cutTractList)):\n",
    "    t = cutTractList[ct]\n",
    "    cutPop += tractPop[t]  #sum up the cut pops\n",
    "    cutVAP += tractVAP[t]\n",
    "    cutHisp += tractHisp[t]\n",
    "    cutBlack += tractBlack[t]\n",
    "    # Now we zero out the pops in the cut tracts\n",
    "    tractPop[t] = 0\n",
    "    tractVAP[t] = 0\n",
    "    tractHisp[t] = 0\n",
    "    tractBlack[t] = 0\n",
    "# Now distribute the pops among the receivers\n",
    "ntR = len(tractReceivers)\n",
    "NTR = float(ntR)\n",
    "for rt in range(ntR) :\n",
    "    t = tractReceivers[rt]\n",
    "    tractPop[t] += cutPop/NTR\n",
    "    tractVAP[t] += cutVAP/NTR\n",
    "    tractHisp[t] += cutHisp/NTR\n",
    "    tractBlack[t] += cutBlack/NTR\n",
    "\n",
    "#             now do the same for the precincts\n",
    "for cp in range(len(cutPrecinctList)):\n",
    "    p = cutPrecinctList[cp]\n",
    "    cutTrump += vtdTrump[p]\n",
    "    cutBiden += vtdBiden[p]\n",
    "        # Now we zero out the pops in the cut precincts\n",
    "    vtdTrump[p] = 0\n",
    "    vtdBiden[p] = 0\n",
    "\n",
    "# Now distribute the pops among the receivers\n",
    "npR = len(precinctReceivers)\n",
    "NPR = float(npR)\n",
    "for rp in range(npR) :\n",
    "    p = precinctReceivers[rp]\n",
    "    vtdTrump[p] += cutTrump/NPR\n",
    "    vtdBiden[p] += cutBiden/NPR\n",
    "print(\"I have finished slicing \",cutPop,\"people (VAP of\",cutVAP,\") and \",cutBiden+cutTrump,\"voters out.\" )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "55419803-eaaf-4181-8848-d8fdad0205b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Now, repeat for southern central tip\n",
    "for geom in tractMAP.geoms:\n",
    "    x,y = geom.exterior.xy\n",
    "    plt.plot(x,y)\n",
    "\n",
    "pt1 = Point(-122.8,37.87)\n",
    "pt2 = Point(-123.3,37.9)\n",
    "pt3 = Point(-123.3,37.5)\n",
    "pt4 = Point(-122.8, 37.5)\n",
    "clipPoly = Polygon([pt1,pt2,pt3,pt4])  #LEFTOVER FROM INDIANA. plan to clip off SW corner near Evansville\n",
    "xc,yc = clipPoly.exterior.xy\n",
    "plt.plot(xc,yc)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "2a56b3e5-803d-425d-8bb6-abfba9aa9716",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "clippable tract 1212 with pop 0\n",
      "I have flagged  1 tracts w pop 0.0  to reassign to tracts...\n",
      "[7618]\n",
      "I have flagged  1 precincts to reassign to precincts...\n",
      "[-88888]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#find all tracts and precincts centered in this clipPoly, flag for cutting\n",
    "# and, ID all nearby tracts and precincts to receive their pops and voters\n",
    "cutTractList = [-99999]\n",
    "cutPrecinctList = [-99999]\n",
    "tractReceivers = [-88888]\n",
    "precinctReceivers = [-88888]\n",
    "popToCut = 0.\n",
    "for t in range(nTracts):\n",
    "    x = tractGeom[t].centroid.x\n",
    "    y = tractGeom[t].centroid.y\n",
    "    if tractGeom[t].intersects(clipPoly) :\n",
    "        print(\"clippable tract\",t,\"with pop\",tractPop[t])\n",
    "        CP = Point(x,y)\n",
    "        if CP.intersects(clipPoly):\n",
    "            isSkippedTract[t] = 1\n",
    "            popToCut += tractPop[t]\n",
    "            if cutTractList == [-99999]:\n",
    "                cutTractList = [t]\n",
    "            else:\n",
    "                cutTractList.append(t)\n",
    "            x,y = tractGeom[t].exterior.xy\n",
    "            plt.plot(x,y)\n",
    "    else:\n",
    "        if tractGeom[t].distance(clipPoly) < 0.05 :\n",
    "            if tractReceivers == [-88888]:\n",
    "                tractReceivers = [t]\n",
    "            else:\n",
    "                tractReceivers.append(t)\n",
    "xp,yp = clipPoly.exterior.xy\n",
    "plt.plot(xp,yp)\n",
    "\n",
    "for p in range(nPrecincts):\n",
    "    x = vtdGeom[p].centroid.x\n",
    "    y = vtdGeom[p].centroid.y\n",
    "    if vtdGeom[p].intersects(clipPoly) :\n",
    "        print(\"clippable precinct\",p,\"with voter Pop\",vtdBiden[p]+vtdTrump[p])\n",
    "        CP = Point(x,y)\n",
    "        if CP.intersects(clipPoly):\n",
    "            isSkippedPrecinct[p] = 1\n",
    "            if cutPrecinctList == [-99999]:\n",
    "                cutPrecinctList = [p]\n",
    "            else:\n",
    "                cutPrecinctList.append(p)\n",
    "    else:\n",
    "        if vtdGeom[p].distance(clipPoly) < 0.05:\n",
    "            if precinctReceivers == [-88888]:\n",
    "                precinctReceivers = [p]\n",
    "            else:\n",
    "                precinctReceivers.append(p)\n",
    "print(\"I have flagged \",len(cutTractList),\"tracts w pop\",popToCut,\" to reassign to tracts...\")\n",
    "print(tractReceivers)\n",
    "print(\"I have flagged \",len(cutPrecinctList),\"precincts to reassign to precincts...\")\n",
    "print(precinctReceivers)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "264c0a29-0366-433f-ae45-63b986566b34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#clipPoly block 2 of 4\n",
    "#visualize the to-be-cut precincts, just to confirm there are really xx precincts up there\n",
    "for p in range(nPrecincts):\n",
    "    if isSkippedPrecinct[p] ==1:\n",
    "        if notPolyVTD[p]==1:\n",
    "            for geom in vtdGeom[p].geoms:\n",
    "                x,y = geom.exterior.xy\n",
    "                plt.plot(x,y)\n",
    "        else:\n",
    "            x,y = vtdGeom[p].exterior.xy\n",
    "            plt.plot(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "34f94200-4cc7-4226-9a6c-d6ae75b3380f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#clipPoly block 3 of 4\n",
    "#now visualize the receivers\n",
    "for pp in range(len(precinctReceivers)):\n",
    "    p = precinctReceivers[pp]\n",
    "    if notPolyVTD[p]==1:\n",
    "        for geom in vtdGeom[p].geoms:\n",
    "            x,y = geom.exterior.xy\n",
    "            plt.plot(x,y)\n",
    "    else:\n",
    "        x,y = vtdGeom[p].exterior.xy\n",
    "        plt.plot(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "9301c018-ac66-4a64-8efe-a839a349e53f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#now visualize the TRACT receivers\n",
    "for tt in range(len(tractReceivers)):\n",
    "    t = tractReceivers[tt]\n",
    "    if notPoly[t]==1:\n",
    "        for geom in tractGeom[t].geoms:\n",
    "            x,y = geom.exterior.xy\n",
    "            plt.plot(x,y)\n",
    "    else:\n",
    "        x,y = tractGeom[t].exterior.xy\n",
    "        plt.plot(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "e8d4b939-2d62-4d7a-a866-7283b3e8e383",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I have finished slicing  263227.0 people (VAP of 201461.0 ) and  133760.0 voters out.\n"
     ]
    }
   ],
   "source": [
    "#now, cut and redistribute\n",
    "cutPop = 0.\n",
    "cutVAP = 0.\n",
    "cutHisp = 0.\n",
    "cutBlack = 0.\n",
    "cutTrump = 0.\n",
    "cutBiden = 0.\n",
    "\n",
    "for ct in range(len(cutTractList)):\n",
    "    t = cutTractList[ct]\n",
    "    cutPop += tractPop[t]  #sum up the cut pops\n",
    "    cutVAP += tractVAP[t]\n",
    "    cutHisp += tractHisp[t]\n",
    "    cutBlack += tractBlack[t]\n",
    "    # Now we zero out the pops in the cut tracts\n",
    "    tractPop[t] = 0\n",
    "    tractVAP[t] = 0\n",
    "    tractHisp[t] = 0\n",
    "    tractBlack[t] = 0\n",
    "# Now distribute the pops among the receivers\n",
    "ntR = len(tractReceivers)\n",
    "NTR = float(ntR)\n",
    "for rt in range(ntR) :\n",
    "    t = tractReceivers[rt]\n",
    "    tractPop[t] += cutPop/NTR\n",
    "    tractVAP[t] += cutVAP/NTR\n",
    "    tractHisp[t] += cutHisp/NTR\n",
    "    tractBlack[t] += cutBlack/NTR\n",
    "\n",
    "#             now do the same for the precincts\n",
    "for cp in range(len(cutPrecinctList)):\n",
    "    p = cutPrecinctList[cp]\n",
    "    cutTrump += vtdTrump[p]\n",
    "    cutBiden += vtdBiden[p]\n",
    "        # Now we zero out the pops in the cut precincts\n",
    "    vtdTrump[p] = 0\n",
    "    vtdBiden[p] = 0\n",
    "\n",
    "# Now distribute the pops among the receivers\n",
    "npR = len(precinctReceivers)\n",
    "NPR = float(npR)\n",
    "for rp in range(npR) :\n",
    "    p = precinctReceivers[rp]\n",
    "    vtdTrump[p] += cutTrump/NPR\n",
    "    vtdBiden[p] += cutBiden/NPR\n",
    "print(\"I have finished slicing \",cutPop,\"people (VAP of\",cutVAP,\") and \",cutBiden+cutTrump,\"voters out.\" )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "84c2cf09-b3ea-4fc2-a55b-62985882836b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#trim down tractMAP.  Normally we would rebuild, but here, we just save the big piece\n",
    "counter = 0\n",
    "for geom in tractMAP.geoms:\n",
    "    if counter == 0:\n",
    "        trimmedMAP = geom\n",
    "    counter +=1\n",
    "\n",
    "x,y = trimmedMAP.exterior.xy\n",
    "plt.plot(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "d4538dfc-7d35-46b4-95c1-c5d93169e971",
   "metadata": {},
   "outputs": [],
   "source": [
    "mapWithIslands = tractMAP #for posterity, save the original map\n",
    "MAP = trimmedMAP  #this is our map prior to buffering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "650cf37d-e11a-4ed3-861b-3f3edc411422",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#What is our distribution of precinct's Trump votes by precinct Biden votes?\n",
    "fig, ax = plt.subplots()\n",
    "ax.set(xlabel=\"Biden votes in this precinct\", ylabel=\"Trump precinct votes\")\n",
    "plt.plot(vtdBiden, vtdTrump, marker='.',linestyle=\"none\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "d40408f3-31eb-4b8a-ad91-4e2eb5f422df",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 0.0 0\n",
      "200 0.0 0\n",
      "400 0.22860425043078691 1741\n",
      "600 0.6170212765957447 47\n",
      "800 0.2838196286472148 754\n",
      "1000 0.2697768762677485 986\n",
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#ALL TRIMS COMPLETE. let's convert the partisan data to the format we use for HD code\n",
    "# in this prototype, we only use 2020 presidential data, but this could be modified\n",
    "vtdGOP = [0.]*nPrecincts  #Each precinct's R/(R+D)\n",
    "vtdPop = [0.]*nPrecincts   #THIS IS VOTER POPULATION\n",
    "vtdArea = [0.]*nPrecincts\n",
    "vtdCPx = [0.]*nPrecincts   #these are centroid x and y of each precinct\n",
    "vtdCPy = [0.]*nPrecincts\n",
    "plotcolor = ['blue']*nPrecincts\n",
    "for p in range(nPrecincts):\n",
    "    vtdPop[p] = vtdTrump[p] + vtdBiden[p] \n",
    "    vtdGOP[p] = vtdTrump[p]/max((vtdTrump[p] + vtdBiden[p]), 0.01)  #avoid divide by zero\n",
    "    if (vtdGOP[p] > 0.40) :\n",
    "        plotcolor[p]='purple'\n",
    "        if (vtdGOP[p] > 0.60) :\n",
    "            plotcolor[p] = 'red'\n",
    "    vtdArea[p] = vtdGeom[p].area\n",
    "    vtdCPx[p] = vtdGeom[p].centroid.x  #not needed except for graphing\n",
    "    vtdCPy[p] = vtdGeom[p].centroid.y   #not needed  \"  \"  \"\n",
    "    if isSkippedPrecinct[p] == 0 and p%100 == 0: #memory drain if we print all\n",
    "        plt.scatter(vtdCPx[p], vtdCPy[p], marker='.',c=plotcolor[p])\n",
    "for p in range (nPrecincts):\n",
    "    if p%200 == 0:\n",
    "        print(p,vtdGOP[p],vtdPop[p])\n",
    "x,y = MAP.exterior.xy\n",
    "plt.plot(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "a1e3f0d2-c21c-46d4-8227-e75dfd5e89b6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "original and buffered map areas are 42.37632909025886 43.10106010854907\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "MAP = trimmedMAP  #committing to the trimmed map (for TN, using convex hull)\n",
    "bufferDistance = 0.02  #do minor buffer for OH\n",
    "origMAP = mapWithIslands    # let's keep a copy of the original map prior to buffering\n",
    "MAPbuffer = MAP.exterior.buffer(bufferDistance, single_sided=True)  #gives a little exterior buffer\n",
    "# MAP = origMAP.convex_hull  #alternate to buffer for weird state shapes\n",
    "bBox = MAP.bounds\n",
    "MAPMinX = bBox[0]  #these four are useful for slicing ops, and are basis for map grid (without buffer)\n",
    "MAPMinY = bBox[1]\n",
    "MAPMaxX = bBox[2]\n",
    "MAPMaxY = bBox[3]\n",
    "\n",
    "MAP = MAP.union(MAPbuffer)  #not buffering for TN\n",
    "print(\"original and buffered map areas are\",origMAP.area,MAP.area)  #same if we didn't buffer\n",
    "x2, y2 = MAP.exterior.xy\n",
    "plt.plot(x2,y2,c=\"green\")\n",
    "x2, y2 = origMAP.exterior.xy\n",
    "#plt.plot(x2,y2,c=\"blue\")\n",
    "plt.show()\n",
    "\n",
    "minTractPop = 10  #was zero to not exclude empty interiors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "8e271f55-e118-4575-bc99-c28c59f435b7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020 population, Trump+Biden voters, lean =  39538218 17116919 0.3509058667735862\n",
      "compare to Census 39538223 Leip has Trump + Biden = 17117157.0 0.3509062865988785\n"
     ]
    }
   ],
   "source": [
    "#let's confirm some population stats - these match 2020 census, USelectionatlas.org :-)\n",
    "censusPop = 39538223\n",
    "atlasTrump = 6006518.\n",
    "atlasBiden = 11110639.\n",
    "\n",
    "print(\"2020 population, Trump+Biden voters, lean = \",np.sum(tractPop),np.sum(vtdPop),stateGOP )\n",
    "print(\"compare to Census\",censusPop,\"Leip has Trump + Biden =\",atlasTrump+atlasBiden,\n",
    "      atlasTrump/(atlasTrump+atlasBiden) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "6c47f717-f208-4a4c-b825-a3181a83c6ee",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "state pop before, after slice operation are 39538218 39538218.0\n",
      "state Trumpers before, after slice opn are 6006428 6006428.0\n"
     ]
    }
   ],
   "source": [
    "#Check on integrity after slicing\n",
    "sumPop = 0.\n",
    "sumTrump = 0.\n",
    "for t in range(nTracts):\n",
    "    if isSkippedTract[t] == 0:\n",
    "        sumPop += tractPop[t]\n",
    "for p in range(nPrecincts):\n",
    "    if isSkippedPrecinct[p] == 0:\n",
    "        sumTrump += vtdTrump[p]\n",
    "print(\"state pop before, after slice operation are\",np.sum(tractPop),sumPop)\n",
    "print(\"state Trumpers before, after slice opn are\",np.sum(vtdTrump),sumTrump)\n",
    "for t in range(nTracts):\n",
    "    if isSkippedTract[t] ==1 and tractPop[t] > 0:  #should not occur\n",
    "        print(\"missed pop for tract, pop, (x,y)\",t,tractPop[t],tractGeom[t].centroid.x,\n",
    "              tractGeom[t].centroid.y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "394c172c-246b-4d2b-8a55-614fe763acc1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#I SHOULD ADD AN \"ISACTIVEGRID\" HERE TO SPEED NON-RECTANGULAR STATES"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "b5334311-b597-4568-88c7-eb3c9d4bdf09",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "map has a total of 528 grids for 52 districts\n",
      "starting grid no 0 at x = -124.2663615, y = 32.74430179545455 \n",
      "starting grid no 5 at x = -124.2663615, y = 34.89899975 \n",
      "starting grid no 10 at x = -124.2663615, y = 37.05369770454545 \n",
      "starting grid no 15 at x = -124.2663615, y = 39.2083956590909 \n",
      "starting grid no 20 at x = -124.2663615, y = 41.36309361363636 \n",
      "starting grid no 25 at x = -123.83507849999998, y = 34.03712056818182 \n",
      "starting grid no 30 at x = -123.83507849999998, y = 36.19181852272728 \n",
      "starting grid no 35 at x = -123.83507849999998, y = 38.346516477272715 \n",
      "starting grid no 40 at x = -123.83507849999998, y = 40.50121443181817 \n",
      "starting grid no 45 at x = -123.4037955, y = 33.17524138636364 \n",
      "starting grid no 50 at x = -123.4037955, y = 35.32993934090909 \n",
      "starting grid no 55 at x = -123.4037955, y = 37.48463729545454 \n",
      "starting grid no 60 at x = -123.4037955, y = 39.63933525 \n",
      "starting grid no 65 at x = -123.4037955, y = 41.79403320454545 \n",
      "starting grid no 70 at x = -122.97251250000001, y = 34.46806015909092 \n",
      "starting grid no 75 at x = -122.9725125, y = 36.622758113636365 \n",
      "starting grid no 80 at x = -122.97251250000001, y = 38.77745606818181 \n",
      "starting grid no 85 at x = -122.97251250000001, y = 40.932154022727275 \n",
      "starting grid no 90 at x = -122.54122949999999, y = 33.60618097727273 \n",
      "starting grid no 95 at x = -122.54122949999999, y = 35.76087893181818 \n",
      "starting grid no 100 at x = -122.54122949999999, y = 37.91557688636363 \n",
      "starting grid no 105 at x = -122.54122949999999, y = 40.070274840909086 \n",
      "starting grid no 110 at x = -122.10994649999999, y = 32.74430179545455 \n",
      "starting grid no 115 at x = -122.10994649999999, y = 34.89899975 \n",
      "starting grid no 120 at x = -122.10994649999999, y = 37.05369770454545 \n",
      "starting grid no 125 at x = -122.10994649999999, y = 39.208395659090904 \n",
      "starting grid no 130 at x = -122.10994649999999, y = 41.36309361363636 \n",
      "starting grid no 135 at x = -121.67866349999998, y = 34.03712056818182 \n",
      "starting grid no 140 at x = -121.67866349999998, y = 36.191818522727274 \n",
      "starting grid no 145 at x = -121.67866349999998, y = 38.34651647727272 \n",
      "starting grid no 150 at x = -121.67866349999998, y = 40.50121443181818 \n",
      "starting grid no 155 at x = -121.24738049999999, y = 33.17524138636364 \n",
      "starting grid no 160 at x = -121.24738049999999, y = 35.32993934090909 \n",
      "starting grid no 165 at x = -121.24738049999999, y = 37.48463729545454 \n",
      "starting grid no 170 at x = -121.24738049999999, y = 39.639335249999995 \n",
      "starting grid no 175 at x = -121.24738049999999, y = 41.79403320454545 \n",
      "starting grid no 180 at x = -120.8160975, y = 34.46806015909091 \n",
      "starting grid no 185 at x = -120.81609749999998, y = 36.622758113636365 \n",
      "starting grid no 190 at x = -120.8160975, y = 38.77745606818181 \n",
      "starting grid no 195 at x = -120.8160975, y = 40.93215402272727 \n",
      "starting grid no 200 at x = -120.38481449999999, y = 33.60618097727273 \n",
      "starting grid no 205 at x = -120.38481449999999, y = 35.76087893181818 \n",
      "starting grid no 210 at x = -120.38481449999999, y = 37.91557688636363 \n",
      "starting grid no 215 at x = -120.38481449999999, y = 40.070274840909086 \n",
      "starting grid no 220 at x = -119.95353149999998, y = 32.74430179545455 \n",
      "starting grid no 225 at x = -119.95353149999998, y = 34.89899975 \n",
      "starting grid no 230 at x = -119.95353149999998, y = 37.05369770454545 \n",
      "starting grid no 235 at x = -119.95353149999998, y = 39.2083956590909 \n",
      "starting grid no 240 at x = -119.95353149999998, y = 41.36309361363636 \n",
      "starting grid no 245 at x = -119.52224849999998, y = 34.03712056818182 \n",
      "starting grid no 250 at x = -119.52224849999998, y = 36.19181852272728 \n",
      "starting grid no 255 at x = -119.52224849999998, y = 38.346516477272715 \n",
      "starting grid no 260 at x = -119.52224849999998, y = 40.50121443181817 \n",
      "starting grid no 265 at x = -119.09096549999998, y = 33.17524138636364 \n",
      "starting grid no 270 at x = -119.09096549999998, y = 35.32993934090909 \n",
      "starting grid no 275 at x = -119.09096549999998, y = 37.48463729545454 \n",
      "starting grid no 280 at x = -119.09096549999998, y = 39.63933525 \n",
      "starting grid no 285 at x = -119.09096549999998, y = 41.79403320454545 \n",
      "starting grid no 290 at x = -118.65968249999999, y = 34.46806015909091 \n",
      "starting grid no 295 at x = -118.65968250000002, y = 36.622758113636365 \n",
      "starting grid no 300 at x = -118.65968249999999, y = 38.77745606818181 \n",
      "starting grid no 305 at x = -118.65968249999999, y = 40.93215402272727 \n",
      "starting grid no 310 at x = -118.22839950000001, y = 33.60618097727273 \n",
      "starting grid no 315 at x = -118.22839950000001, y = 35.76087893181818 \n",
      "starting grid no 320 at x = -118.22839950000001, y = 37.91557688636363 \n",
      "starting grid no 325 at x = -118.22839950000001, y = 40.070274840909086 \n",
      "starting grid no 330 at x = -117.7971165, y = 32.74430179545455 \n",
      "starting grid no 335 at x = -117.7971165, y = 34.89899975 \n",
      "starting grid no 340 at x = -117.7971165, y = 37.05369770454545 \n",
      "starting grid no 345 at x = -117.7971165, y = 39.2083956590909 \n",
      "starting grid no 350 at x = -117.7971165, y = 41.36309361363636 \n",
      "starting grid no 355 at x = -117.3658335, y = 34.03712056818182 \n",
      "starting grid no 360 at x = -117.3658335, y = 36.19181852272728 \n",
      "starting grid no 365 at x = -117.3658335, y = 38.346516477272715 \n",
      "starting grid no 370 at x = -117.3658335, y = 40.50121443181817 \n",
      "starting grid no 375 at x = -116.9345505, y = 33.17524138636364 \n",
      "starting grid no 380 at x = -116.9345505, y = 35.32993934090909 \n",
      "starting grid no 385 at x = -116.9345505, y = 37.48463729545454 \n",
      "starting grid no 390 at x = -116.9345505, y = 39.63933525 \n",
      "starting grid no 395 at x = -116.9345505, y = 41.79403320454545 \n",
      "starting grid no 400 at x = -116.50326749999999, y = 34.46806015909092 \n",
      "starting grid no 405 at x = -116.50326749999999, y = 36.622758113636365 \n",
      "starting grid no 410 at x = -116.50326749999999, y = 38.77745606818181 \n",
      "starting grid no 415 at x = -116.50326749999999, y = 40.932154022727275 \n",
      "starting grid no 420 at x = -116.07198449999999, y = 33.60618097727273 \n",
      "starting grid no 425 at x = -116.07198449999999, y = 35.76087893181818 \n",
      "starting grid no 430 at x = -116.07198449999999, y = 37.91557688636363 \n",
      "starting grid no 435 at x = -116.07198449999999, y = 40.070274840909086 \n",
      "starting grid no 440 at x = -115.6407015, y = 32.74430179545455 \n",
      "starting grid no 445 at x = -115.6407015, y = 34.89899975 \n",
      "starting grid no 450 at x = -115.6407015, y = 37.05369770454545 \n",
      "starting grid no 455 at x = -115.6407015, y = 39.208395659090904 \n",
      "starting grid no 460 at x = -115.6407015, y = 41.36309361363636 \n",
      "starting grid no 465 at x = -115.20941849999998, y = 34.03712056818182 \n",
      "starting grid no 470 at x = -115.20941849999998, y = 36.191818522727274 \n",
      "starting grid no 475 at x = -115.20941849999998, y = 38.34651647727272 \n",
      "starting grid no 480 at x = -115.20941849999998, y = 40.50121443181818 \n",
      "starting grid no 485 at x = -114.77813549999998, y = 33.17524138636364 \n",
      "starting grid no 490 at x = -114.77813549999998, y = 35.32993934090909 \n",
      "starting grid no 495 at x = -114.77813549999998, y = 37.48463729545454 \n",
      "starting grid no 500 at x = -114.77813549999998, y = 39.639335249999995 \n",
      "starting grid no 505 at x = -114.77813549999998, y = 41.79403320454545 \n",
      "starting grid no 510 at x = -114.34685249999997, y = 34.46806015909091 \n",
      "starting grid no 515 at x = -114.34685249999998, y = 36.622758113636365 \n",
      "starting grid no 520 at x = -114.34685249999997, y = 38.77745606818181 \n",
      "starting grid no 525 at x = -114.34685249999997, y = 40.93215402272727 \n",
      "done building grids. avgGridDensity, maxGridDensity,nPopulatedGrids = 790835.355367433 33088382.40178541 269.0\n"
     ]
    }
   ],
   "source": [
    "# this section - ESTIMATE POP'N DENSITY at scale of 1/3 of district length\n",
    "# also, IDENTIFY WHICH TRACTS and VTD's INTERSECT EACH GRID to speed later intersection searches by grid \n",
    "# (above sections already pulled in Tract and Precinct geometry and demographic data, built an overall map)\n",
    "nDistricts = 52   #CA congressional\n",
    "avgDistrictPop = np.sum(tractPop) / float(nDistricts)\n",
    "#MAPMaxX = -80.   #In most state maps, we figure this out from the bounding box of the convex hull; see above.\n",
    "#MAPMaxY = 31.1   # ... but for Florida, we will do manually\n",
    "#MAPMinX = -87.0\n",
    "#MAPMinY = 25.5\n",
    "stateWidth = float(MAPMaxX - MAPMinX)\n",
    "stateHeight = float(MAPMaxY - MAPMinY)\n",
    "stateWHRatio = stateWidth / stateHeight\n",
    "G = 3  #adjustable parameter; G*G = number of grids that fit in an average district\n",
    "nGridsX = int( G*round((nDistricts*stateWHRatio)**0.5,0) )   #OK to have empty grids for a non-rectglr state\n",
    "nGridsY = int(round(nGridsX / stateWHRatio,0) )  #so grids are square even if state has high aspect ratio\n",
    "nGrids = int(nGridsX*nGridsY)\n",
    "print(\"map has a total of {0} grids for {1} districts\".format(nGrids,nDistricts) )\n",
    "nGridPrecincts = [0]*nGrids # will store how many precincts intersect with each grid square\n",
    "nGridTracts = [0]*nGrids    # same, but for tracts\n",
    "gridPrecinctNo = [[0]*nPrecincts for gridNo in range(nGrids) ] # initialize a list of VTDs that intersect with each grid square\n",
    "gridTractNo = [[0]*nTracts for gridNo in range(nGrids) ] # initialize a list of tracts that intersect with each grid square\n",
    "\n",
    "gridPop = [0.]*nGrids #will store approx total population for this grid square\n",
    "gridDensity = [0.]*nGrids\n",
    "gridGeom = [Polygon([(0,0),(0,1),(1,0)])]*nGrids  #initialize grid geometry\n",
    "gridWidth = stateWidth /nGridsX        #geo length of a grid's side length\n",
    "gridHeight = stateHeight /nGridsY    \n",
    "\n",
    "for nG in range (nGrids) : #  create polygon shape for each grid square, compute grid-square population density\n",
    "    x = int(nG/nGridsY)\n",
    "    y = int(nG % nGridsY)\n",
    "    point1 = Point(x*gridWidth+MAPMinX,y*gridHeight+MAPMinY)\n",
    "    point2 = Point((x+1)*gridWidth+MAPMinX, y*gridHeight+MAPMinY)\n",
    "    point3 = Point((x+1)*gridWidth+MAPMinX, (y+1)*gridHeight+MAPMinY)\n",
    "    point4 = Point(x*gridWidth+MAPMinX, (y+1)*gridHeight+MAPMinY)\n",
    "    gridGeom[nG] = Polygon([point1, point2, point3, point4])\n",
    "    if (nG %5 == 0): #print occasionally, should take about one second per grid\n",
    "        print(\"starting grid no {0} at x = {1}, y = {2} \".format(nG,gridGeom[nG].centroid.x,gridGeom[nG].centroid.y) )\n",
    "    counter = 0\n",
    "    #    Now for each grid square, find intersxn with all polygons, total the intersection population\n",
    "    #    Also, create 2 lists: of TRACTS and precincts that intersect each grid (efficiency shortcut)\n",
    "    \n",
    "    if( gridGeom[nG].intersection(MAP).area > 0.0001) : #don't bother w grids off the map\n",
    "        for t in range(nTracts):\n",
    "            # if (t%3000 == 0) :\n",
    "            #    print (\"grid {0}, tract no {1}, ({2},{3})\".format(nG,t,tractGeom[t].centroid.x,tractGeom[t].centroid.y) )\n",
    "            intersxnArea = 0.\n",
    "            if isSkippedTract[t] == 0:\n",
    "                if (notPoly[t] == 0) :  # tract is a simple polygon\n",
    "                    intersxnArea = gridGeom[nG].intersection(tractGeom[t]).area  #replaced tractGeom w cleanedPoly\n",
    "                else : #tract is a multiPolygon, do the polygon intersections individually\n",
    "                    print(\"I think tract\",t,\"is a multiPolygon\")\n",
    "                    for geom in tractGeom[t].geoms :\n",
    "                        intersxnArea += gridGeom[nG].intersection(geom).area\n",
    "                if (intersxnArea > 0 and tractPop[t] > minTractPop) : # this tract is at least partially in this grid and populated \n",
    "                    if (tractArea[t] == 0):  #should not happen, but debugging\n",
    "                        print(t,tractGeom[t].centroid.x, tractGeom[t].centroid.y)  #debug print\n",
    "                    gridPop[nG] += tractPop[t]*intersxnArea/tractArea[t]\n",
    "                    if tractPop[t] > (1.0 * avgDistrictPop) :  #flag if we have a mega tract\n",
    "                        uhoh = input(\"Uh oh! We have a tract that's bigger than a district.  What now?\")\n",
    "                    else :\n",
    "                        gridTractNo[nG][counter] = t  #add this tract to this grid's list, update the no of tracts in grid\n",
    "                        counter +=1            \n",
    "                        nGridTracts[nG] = counter\n",
    "        # OK, now, loop over PRECINCTS to develop each grid's list of precincts (prev loop was for tracts)\n",
    "        counter = 0\n",
    "        for p in range(nPrecincts):\n",
    "            intersxnArea = 0.\n",
    "            if isSkippedPrecinct[t] == 0:\n",
    "                if (notPolyVTD[p] == 0) :  # precinct is a simple polygon\n",
    "                    intersxnArea = gridGeom[nG].intersection(vtdGeom[p]).area  #replaced tractGeom w cleanedPoly\n",
    "                else : #precinct is a multiPolygon, do the polygon intersections individually\n",
    "                    for geom in vtdGeom[p].geoms :\n",
    "                        intersxnArea += gridGeom[nG].intersection(geom).area\n",
    "                intersxnArea = gridGeom[nG].intersection(vtdGeom[p]).area\n",
    "                if (intersxnArea > 0 and vtdPop[p] >0) : # this precinct is at least partially in this grid and recorded votes                 \n",
    "                    gridPrecinctNo[nG][counter] = p  #add this precinct to this grid's list, update the no of tracts in grid\n",
    "                    counter +=1            \n",
    "                    nGridPrecincts[nG] = counter\n",
    "    gridDensity[nG] = gridPop[nG] / gridGeom[nG].area  #finished loop over tracts & vtd's.  Calceach grid's population density    \n",
    "\n",
    "minGridPop = np.min(gridPop)\n",
    "# avgGridPop = np.mean(gridPop)   #see below for explicit averaging, since there are so many empty grids\n",
    "maxGridPop = np.max(gridPop)\n",
    "nPopulatedGrids = 0.\n",
    "totPopulatedGridArea = 0.\n",
    "for nG in range(nGrids) :\n",
    "    if gridPop[nG] > 0. :\n",
    "        nPopulatedGrids +=1   #****I should add an isActiveGrid here***\n",
    "        totPopulatedGridArea += gridGeom[nG].area\n",
    "avgGridPop = np.sum(tractPop) / nPopulatedGrids\n",
    "avgGridDensity = np.sum(tractPop) / totPopulatedGridArea\n",
    "#avgGridDensity = np.average(gridDensity) #avgGridPop / (gridPL * gridPL) #these densities help home district algorithm\n",
    "maxGridDensity = np.max(gridDensity)\n",
    "print(\"done building grids. avgGridDensity, maxGridDensity,nPopulatedGrids =\",avgGridDensity,maxGridDensity,nPopulatedGrids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "808f513f-21af-4b03-8061-fdeeed33dafd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here is a heat map of grid density \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<function matplotlib.pyplot.show(close=None, block=None)>"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"here is a heat map of grid density \")\n",
    "xyGridDensity = [[0.]*nGridsX for x in range (nGridsY) ]   #flipping x and y to get right orientation in pixel grid\n",
    "for nG in range (nGrids) : #  create polygon shape for each grid square, compute grid-square population density\n",
    "    x = int(nG % nGridsY)\n",
    "    y = int(nG / nGridsY)\n",
    "    if gridDensity[nG] > 0 :  #avoid log zero\n",
    "        xyGridDensity[x][y]=np.log(gridDensity[nG])\n",
    "c=plt.pcolormesh(xyGridDensity)\n",
    "plt.colorbar(c)\n",
    "plt.show"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "4013f80b-4fc8-40a1-b708-ee29c29b3ffe",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5.454634510064074e-09 2.176944999991544e-06\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(np.min(vtdArea), np.min(tractArea))\n",
    "minTractPop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "ab450500-f1a4-4292-a2fe-71eb2217121d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I am working on tract number 0 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 19 3.0 0 141.7 0.457 119974.6\n",
      "I am working on tract number 20 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 26 2.0 1 90.0 0.1824 74437.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 26 3.0 1 90.0 0.346 74437.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 26 6.0 0 86.3 0.1866 70767.9\n",
      "7 yoyos for tract,wedge,wedgePop,r= 36 2 708384.661844664 1.8475\n",
      "8 yoyos for tract,wedge,wedgePop,r= 36 2 94917.04964130244 0.9238\n",
      "9 yoyos for tract,wedge,wedgePop,r= 36 2 655923.1373753493 1.7421\n",
      "9 yoyos for tract,wedge,wedgePop,r= 36 2 236491.23301524727 1.3329\n",
      "loop31.0, tr36,wedgePops674558.18, 189701.4, 190019.0, 104878.1, 189959.6, Overedge?0, 0, 0, 0, ,Satisfied?1101,yoyo?2292 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0077, 190087.6,0.0005, 190087.6,-0.2046, 190087.6,0.0026\n",
      "10 yoyos for tract,wedge,wedgePop,r= 36 2 104878.11858093075 1.1283\n",
      "loop32.0, tr36,wedgePops791559.87, 189701.4, 190019.0, 221879.8, 189959.6, Overedge?0, 0, 0, 0, ,Satisfied?1101,yoyo?22102 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0077, 190087.6,0.0005, 190087.6,0.1023, 190087.6,0.0026\n",
      "11 yoyos for tract,wedge,wedgePop,r= 36 2 221879.8114115561 1.2306\n",
      "loop33.0, tr36,wedgePops724188.84, 189701.4, 190019.0, 154508.8, 189959.6, Overedge?0, 0, 0, 0, ,Satisfied?1101,yoyo?22112 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0077, 190087.6,0.0005, 190087.6,-0.0511, 190087.6,0.0026\n",
      "12 yoyos for tract,wedge,wedgePop,r= 36 2 154508.78267684946 1.1795\n",
      "loop34.0, tr36,wedgePops761047.59, 189701.4, 190019.0, 191367.5, 189959.6, Overedge?0, 0, 0, 0, ,Satisfied?1101,yoyo?22122 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0077, 190087.6,0.0005, 190087.6,0.0256, 190087.6,0.0026\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 38 5.0 3 90.0 2.7267 220613.6\n",
      "I am working on tract number 40 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 49 3.0 3 90.0 0.2096 111672.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 53 3.0 3 90.0 0.2683 154077.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 53 4.0 3 90.0 0.3129 154077.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 53 5.0 3 90.0 0.3649 154077.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 54 6.0 0 137.0 0.3862 107091.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 54 7.0 0 137.0 0.5787 107091.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 54 8.0 0 137.0 0.8671 107091.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 55 2.0 1 90.0 0.1882 25572.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 55 5.0 0 90.1 0.1918 24542.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 58 3.0 3 90.0 1.1018 204457.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 58 4.0 3 90.0 1.0427 204457.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 58 5.0 3 90.0 0.9867 204457.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 58 6.0 3 90.0 0.9338 204457.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 58 7.0 3 90.0 0.8837 204457.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 58 8.0 3 90.0 0.8362 204457.5\n",
      "7 yoyos for tract,wedge,wedgePop,r= 58 1 1880102.2836362408 3.1718\n",
      "7 yoyos for tract,wedge,wedgePop,r= 58 1 780058.7555653944 1.5859\n",
      "8 yoyos for tract,wedge,wedgePop,r= 58 1 13647.878275724011 0.793\n",
      "7 yoyos for tract,wedge,wedgePop,r= 58 3 198416.17040244435 0.5048\n",
      "9 yoyos for tract,wedge,wedgePop,r= 58 1 663230.0529135013 1.2921\n",
      "8 yoyos for tract,wedge,wedgePop,r= 58 3 8007.239538052992 0.2524\n",
      "10 yoyos for tract,wedge,wedgePop,r= 58 1 70637.44400627201 1.0425\n",
      "9 yoyos for tract,wedge,wedgePop,r= 58 3 200379.80286863362 0.5432\n",
      "11 yoyos for tract,wedge,wedgePop,r= 58 1 465885.3544618587 1.1673\n",
      "10 yoyos for tract,wedge,wedgePop,r= 58 3 100837.4801609297 0.3978\n",
      "11 yoyos for tract,wedge,wedgePop,r= 58 1 212344.62315867606 1.1049\n",
      "11 yoyos for tract,wedge,wedgePop,r= 58 3 194715.01379483065 0.4705\n",
      "12 yoyos for tract,wedge,wedgePop,r= 58 1 127366.76729753154 1.0737\n",
      "12 yoyos for tract,wedge,wedgePop,r= 58 3 158329.7405749854 0.4342\n",
      "12 yoyos for tract,wedge,wedgePop,r= 58 1 163121.3175159296 1.0893\n",
      "13 yoyos for tract,wedge,wedgePop,r= 58 3 190594.71111700052 0.4523\n",
      "12 yoyos for tract,wedge,wedgePop,r= 58 1 186027.96674884806 1.0971\n",
      "14 yoyos for tract,wedge,wedgePop,r= 58 3 175514.19854613423 0.4433\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_54/3834838.py:66: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  minR = (avgDistrictPop / maxStartDensity / pi)**0.5   # conservative estimated radius of this tract's district\n",
      "/tmp/ipykernel_54/3834838.py:99: RuntimeWarning: invalid value encountered in multiply\n",
      "  wedgePop[nW] = tractPop[t]* wedgePoly.area/max(tractArea[t],minTractArea)  #max prevents rare div-by-zero\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I am working on tract number 60 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 70 3.0 3 90.0 0.374 59403.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 73 7.0 3 44.9 1.1534 255478.7\n",
      "I am working on tract number 80 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 81 2.0 1 90.0 0.1465 33231.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 86 2.0 1 90.0 0.2839 10458.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 87 2.0 1 90.0 0.2001 10032.3\n",
      "7 yoyos for tract,wedge,wedgePop,r= 87 3 253640.08047857866 0.8111\n",
      "8 yoyos for tract,wedge,wedgePop,r= 87 3 53602.664621120086 0.4055\n",
      "9 yoyos for tract,wedge,wedgePop,r= 87 3 258747.12670025465 0.8459\n",
      "10 yoyos for tract,wedge,wedgePop,r= 87 3 104770.05051012262 0.6257\n",
      "10 yoyos for tract,wedge,wedgePop,r= 87 3 194252.78856140567 0.7358\n",
      "10 yoyos for tract,wedge,wedgePop,r= 87 3 242607.0825136515 0.7909\n",
      "11 yoyos for tract,wedge,wedgePop,r= 87 3 256709.87220189118 0.8184\n",
      "I am working on tract number 100 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 110 3.0 3 90.0 0.4982 167678.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 110 4.0 3 90.0 0.5466 167678.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 110 5.0 3 90.0 0.5997 167678.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 110 6.0 3 90.0 0.6579 167678.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 110 10.0 0 138.1 0.5237 165962.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 110 11.0 0 138.1 0.5789 165962.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 110 12.0 0 138.1 0.6398 165962.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 110 13.0 0 138.1 0.7072 165962.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 110 14.0 0 138.1 0.7817 165962.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 110 15.0 0 138.1 0.864 165962.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 110 16.0 0 138.1 0.9551 165962.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 113 3.0 0 90.0 0.2003 133213.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 113 4.0 0 90.0 0.2587 133213.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 113 5.0 0 90.0 0.3342 133213.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 113 6.0 0 90.0 0.4317 133213.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 116 3.0 1 90.0 0.2283 94303.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 116 4.0 1 90.0 0.3721 94303.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 118 2.0 2 90.0 0.1445 51817.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 118 3.0 2 90.0 0.343 51817.6\n",
      "I am working on tract number 120 of 9129 tracts\n",
      "I am working on tract number 140 of 9129 tracts\n",
      "I am working on tract number 160 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 173 2.0 0 90.0 0.4291 3561.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 174 3.0 0 90.0 0.6118 131783.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 174 7.0 0 140.8 0.6524 164382.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 174 8.0 0 140.8 0.7261 164382.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 174 9.0 0 140.8 0.8082 164382.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 174 10.0 0 140.8 0.8995 164382.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 174 11.0 0 140.8 1.0012 164382.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 174 12.0 0 140.8 1.1143 164382.6\n",
      "7 yoyos for tract,wedge,wedgePop,r= 178 3 1020955.1376242351 2.1011\n",
      "8 yoyos for tract,wedge,wedgePop,r= 178 3 151640.56559557852 1.0505\n",
      "9 yoyos for tract,wedge,wedgePop,r= 178 3 1036725.7916233459 2.1226\n",
      "9 yoyos for tract,wedge,wedgePop,r= 178 3 666749.4100847046 1.5866\n",
      "9 yoyos for tract,wedge,wedgePop,r= 178 3 499731.21836158854 1.3186\n",
      "9 yoyos for tract,wedge,wedgePop,r= 178 3 336564.4962851431 1.1846\n",
      "10 yoyos for tract,wedge,wedgePop,r= 178 3 195609.73977629514 1.1175\n",
      "11 yoyos for tract,wedge,wedgePop,r= 178 3 259479.47160354332 1.1511\n",
      "I am working on tract number 180 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 180 2.0 3 90.0 0.2562 70964.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 180 3.0 3 90.0 0.5009 70964.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 186 3.0 3 90.0 1.1208 24514.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 191 3.0 0 90.0 0.3349 60074.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 192 2.0 0 90.0 0.2716 11199.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 192 6.0 0 83.5 0.2954 9443.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 192 10.0 0 83.5 2.0016 198272.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 192 11.0 0 83.5 1.939 198272.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 192 12.0 0 83.5 1.8783 198272.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 192 13.0 0 83.5 1.8195 198272.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 192 14.0 0 83.5 1.7626 198272.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 192 15.0 0 83.5 1.7075 198272.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 192 17.0 1 96.5 0.8527 88551.5\n",
      "7 yoyos for tract,wedge,wedgePop,r= 192 1 261820.4135785639 1.2103\n",
      "8 yoyos for tract,wedge,wedgePop,r= 192 1 88551.46818863135 0.6052\n",
      "9 yoyos for tract,wedge,wedgePop,r= 192 1 261820.4135785541 1.329\n",
      "10 yoyos for tract,wedge,wedgePop,r= 192 1 123403.17117212937 0.9671\n",
      "11 yoyos for tract,wedge,wedgePop,r= 192 1 261820.4135785541 1.148\n",
      "11 yoyos for tract,wedge,wedgePop,r= 192 1 203368.55160629936 1.0576\n",
      "12 yoyos for tract,wedge,wedgePop,r= 192 1 164158.70708455605 1.0123\n",
      "12 yoyos for tract,wedge,wedgePop,r= 192 1 179852.34572262564 1.0349\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 194 3.0 3 90.0 0.3647 56809.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 194 7.0 0 83.3 0.4373 47431.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 194 11.0 1 96.7 0.7148 134395.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 195 3.0 0 90.0 0.3279 254224.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 198 6.0 0 132.5 0.5145 133303.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 198 7.0 0 132.5 0.6644 133303.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 198 8.0 0 132.5 0.8579 133303.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 199 9.0 0 135.1 1.1579 275617.3\n",
      "I am working on tract number 200 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 201 7.0 0 90.0 0.6441 130662.9\n",
      "7 yoyos for tract,wedge,wedgePop,r= 214 0 203991.7167685973 0.5586\n",
      "8 yoyos for tract,wedge,wedgePop,r= 214 0 65813.19424553434 0.2793\n",
      "9 yoyos for tract,wedge,wedgePop,r= 214 0 203311.5444510422 0.5501\n",
      "10 yoyos for tract,wedge,wedgePop,r= 214 0 138547.5315425497 0.4147\n",
      "10 yoyos for tract,wedge,wedgePop,r= 214 0 159821.77862505696 0.4824\n",
      "11 yoyos for tract,wedge,wedgePop,r= 214 0 198465.45856525816 0.5162\n",
      "12 yoyos for tract,wedge,wedgePop,r= 214 0 184081.094180273 0.4993\n",
      "I am working on tract number 220 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 220 2.0 3 90.0 0.2809 28124.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 220 5.0 2 452.4 0.2834 27599.0\n",
      "7 yoyos for tract,wedge,wedgePop,r= 228 1 212039.35254044938 3.1406\n",
      "8 yoyos for tract,wedge,wedgePop,r= 228 1 52779.941053211805 1.5703\n",
      "9 yoyos for tract,wedge,wedgePop,r= 228 1 236714.7403007547 3.3475\n",
      "10 yoyos for tract,wedge,wedgePop,r= 228 1 105333.60611221023 2.4589\n",
      "10 yoyos for tract,wedge,wedgePop,r= 228 1 128015.88599756136 2.9032\n",
      "11 yoyos for tract,wedge,wedgePop,r= 228 1 202031.96488153847 3.1253\n",
      "12 yoyos for tract,wedge,wedgePop,r= 228 1 140112.65005698556 3.0143\n",
      "12 yoyos for tract,wedge,wedgePop,r= 228 1 169802.70824005088 3.0698\n",
      "12 yoyos for tract,wedge,wedgePop,r= 228 1 183150.73167956906 3.0976\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 231 6.0 2 90.0 3.6101 195209.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 231 7.0 2 90.0 3.5386 195209.0\n",
      "I am working on tract number 240 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 242 3 540888.1228426785 0.9304\n",
      "8 yoyos for tract,wedge,wedgePop,r= 242 3 109404.45583744755 0.4652\n",
      "9 yoyos for tract,wedge,wedgePop,r= 242 3 543630.039646294 0.9392\n",
      "9 yoyos for tract,wedge,wedgePop,r= 242 3 466787.47332914546 0.7022\n",
      "9 yoyos for tract,wedge,wedgePop,r= 242 3 282074.1779324266 0.5837\n",
      "10 yoyos for tract,wedge,wedgePop,r= 242 3 169247.60760370933 0.5244\n",
      "11 yoyos for tract,wedge,wedgePop,r= 242 3 219361.7998477971 0.5541\n",
      "7 yoyos for tract,wedge,wedgePop,r= 245 3 915628.9685994346 1.6451\n",
      "8 yoyos for tract,wedge,wedgePop,r= 245 3 34687.06598852808 0.8225\n",
      "9 yoyos for tract,wedge,wedgePop,r= 245 3 934274.509184797 1.691\n",
      "9 yoyos for tract,wedge,wedgePop,r= 245 3 676154.6616434787 1.2567\n",
      "9 yoyos for tract,wedge,wedgePop,r= 245 3 358842.3781483988 1.0396\n",
      "loop31.0, tr245,wedgePops613402.25, 144734.7, 204971.5, 204722.1, 58973.9, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?0019 \n",
      "   targetWP, latest drx4 are tWP,dr, 205205.2,0.9104, 205205.2,0.0022, 205205.2,0.0006, 205205.2,-0.1086\n",
      "10 yoyos for tract,wedge,wedgePop,r= 245 3 58973.89670732198 0.9311\n",
      "loop32.0, tr245,wedgePops742126.87, 144734.7, 204971.5, 204722.1, 187698.5, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?00110 \n",
      "   targetWP, latest drx4 are tWP,dr, 205205.2,0.9104, 205205.2,0.0022, 205205.2,0.0006, 205205.2,0.0543\n",
      "10 yoyos for tract,wedge,wedgePop,r= 245 3 187698.51223532754 0.9854\n",
      "loop33.0, tr245,wedgePops821876.66, 144734.7, 204971.5, 204722.1, 267448.3, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?00110 \n",
      "   targetWP, latest drx4 are tWP,dr, 205205.2,0.9104, 205205.2,0.0022, 205205.2,0.0006, 205205.2,0.0271\n",
      "11 yoyos for tract,wedge,wedgePop,r= 245 3 267448.3068108342 1.0125\n",
      "loop34.0, tr245,wedgePops782593.95, 144734.7, 204971.5, 204722.1, 228165.6, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?00111 \n",
      "   targetWP, latest drx4 are tWP,dr, 205205.2,0.9104, 205205.2,0.0022, 205205.2,0.0006, 205205.2,-0.0136\n",
      "11 yoyos for tract,wedge,wedgePop,r= 245 3 228165.59077865042 0.9989\n",
      "loop35.0, tr245,wedgePops762268.18, 144734.7, 204971.5, 204722.1, 207839.8, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?00111 \n",
      "   targetWP, latest drx4 are tWP,dr, 205205.2,0.9104, 205205.2,0.0022, 205205.2,0.0006, 205205.2,-0.0068\n",
      "I am working on tract number 260 of 9129 tracts\n",
      "I am working on tract number 280 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 281 7.0 1 90.0 0.5561 208084.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 288 4.0 2 90.0 0.6763 177161.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 288 14.0 2 90.0 0.6183 177161.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 288 15.0 2 90.0 0.6515 177161.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 288 20.0 2 90.0 0.6789 177161.6\n",
      "7 yoyos for tract,wedge,wedgePop,r= 288 2 268493.7430956339 0.9129\n",
      "8 yoyos for tract,wedge,wedgePop,r= 288 2 175246.43089356125 0.4565\n",
      "9 yoyos for tract,wedge,wedgePop,r= 288 2 270553.9358018715 1.4512\n",
      "9 yoyos for tract,wedge,wedgePop,r= 288 2 269458.3549266254 0.9538\n",
      "10 yoyos for tract,wedge,wedgePop,r= 288 2 177850.53640414198 0.7052\n",
      "11 yoyos for tract,wedge,wedgePop,r= 288 2 253774.12142570294 0.8295\n",
      "11 yoyos for tract,wedge,wedgePop,r= 288 2 206599.40390093793 0.7673\n",
      "12 yoyos for tract,wedge,wedgePop,r= 288 2 186749.9727974067 0.7362\n",
      "13 yoyos for tract,wedge,wedgePop,r= 288 2 198108.10251789948 0.7518\n",
      "loop31.0, tr288,wedgePops761743.67, 189834.7, 189836.5, 192422.2, 189650.3, Overedge?0, 0, 0, 0, ,Satisfied?1101,yoyo?00130 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0001, 190087.6,0.0015, 190087.6,-0.0078, 190087.6,0.0008\n",
      "7 yoyos for tract,wedge,wedgePop,r= 295 0 523346.26912272203 1.9812\n",
      "I am working on tract number 300 of 9129 tracts\n",
      "I am working on tract number 320 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 333 1 250532.08741712902 1.4429\n",
      "8 yoyos for tract,wedge,wedgePop,r= 333 1 442818.4073008337 5.1532\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 333 20.0 1 53.0 3.298 442818.4\n",
      "8 yoyos for tract,wedge,wedgePop,r= 333 1 442818.4073008337 3.298\n",
      "8 yoyos for tract,wedge,wedgePop,r= 333 1 419492.75087198446 2.3704\n",
      "8 yoyos for tract,wedge,wedgePop,r= 333 1 407214.4992804135 1.9066\n",
      "9 yoyos for tract,wedge,wedgePop,r= 333 1 262523.20814013906 1.6748\n",
      "10 yoyos for tract,wedge,wedgePop,r= 333 1 371098.5856287674 1.7907\n",
      "11 yoyos for tract,wedge,wedgePop,r= 333 1 313798.6792322857 1.7327\n",
      "12 yoyos for tract,wedge,wedgePop,r= 333 1 343315.71895645827 1.7617\n",
      "13 yoyos for tract,wedge,wedgePop,r= 333 1 329217.7517422078 1.7472\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 336 2.0 0 90.0 0.2612 74117.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 336 6.0 0 116.8 1.1493 104525.5\n",
      "I am working on tract number 340 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 356 0 774153.1690017851 1.1197\n",
      "7 yoyos for tract,wedge,wedgePop,r= 356 0 204938.12328705064 0.5598\n",
      "8 yoyos for tract,wedge,wedgePop,r= 356 0 2367.590918848582 0.2799\n",
      "8 yoyos for tract,wedge,wedgePop,r= 356 0 66238.10208702761 0.5126\n",
      "9 yoyos for tract,wedge,wedgePop,r= 356 0 397805.959961 0.629\n",
      "9 yoyos for tract,wedge,wedgePop,r= 356 0 238262.18440708096 0.5708\n",
      "10 yoyos for tract,wedge,wedgePop,r= 356 0 148977.1801660488 0.5417\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 357 12.0 0 90.0 1.6314 423210.1\n",
      "7 yoyos for tract,wedge,wedgePop,r= 357 0 313267.4363136019 1.1595\n",
      "8 yoyos for tract,wedge,wedgePop,r= 357 0 5463.374088732409 0.5797\n",
      "9 yoyos for tract,wedge,wedgePop,r= 357 0 423208.36448573985 1.6218\n",
      "9 yoyos for tract,wedge,wedgePop,r= 357 0 271755.5508630284 1.1008\n",
      "10 yoyos for tract,wedge,wedgePop,r= 357 0 10248.302882088406 0.8403\n",
      "10 yoyos for tract,wedge,wedgePop,r= 357 0 46754.24484335461 0.9705\n",
      "10 yoyos for tract,wedge,wedgePop,r= 357 0 141757.23024398158 1.0356\n",
      "11 yoyos for tract,wedge,wedgePop,r= 357 0 215885.14279684806 1.0682\n",
      "12 yoyos for tract,wedge,wedgePop,r= 357 0 185710.40233170925 1.0519\n",
      "13 yoyos for tract,wedge,wedgePop,r= 357 0 202049.64337108727 1.0601\n",
      "13 yoyos for tract,wedge,wedgePop,r= 357 0 194588.46635517676 1.056\n",
      "I am working on tract number 360 of 9129 tracts\n",
      "I am working on tract number 380 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 388 1 203652.89247620333 1.8961\n",
      "8 yoyos for tract,wedge,wedgePop,r= 388 1 90074.81580022603 0.9481\n",
      "9 yoyos for tract,wedge,wedgePop,r= 388 1 267787.08076365595 2.434\n",
      "10 yoyos for tract,wedge,wedgePop,r= 388 1 104608.32394913392 1.6911\n",
      "11 yoyos for tract,wedge,wedgePop,r= 388 1 250278.57302430357 2.0626\n",
      "11 yoyos for tract,wedge,wedgePop,r= 388 1 199099.91407630497 1.8768\n",
      "12 yoyos for tract,wedge,wedgePop,r= 388 1 118840.67161932163 1.7839\n",
      "12 yoyos for tract,wedge,wedgePop,r= 388 1 159954.77992755163 1.8304\n",
      "12 yoyos for tract,wedge,wedgePop,r= 388 1 183196.75493488924 1.8536\n",
      "7 yoyos for tract,wedge,wedgePop,r= 389 1 248574.6059057895 1.9367\n",
      "8 yoyos for tract,wedge,wedgePop,r= 389 1 83898.5376104018 0.9683\n",
      "9 yoyos for tract,wedge,wedgePop,r= 389 1 269204.31769174396 2.3924\n",
      "10 yoyos for tract,wedge,wedgePop,r= 389 1 105498.4677799636 1.6804\n",
      "11 yoyos for tract,wedge,wedgePop,r= 389 1 257174.8901097504 2.0364\n",
      "12 yoyos for tract,wedge,wedgePop,r= 389 1 181818.7242207773 1.8584\n",
      "13 yoyos for tract,wedge,wedgePop,r= 389 1 250073.5372046056 1.9474\n",
      "13 yoyos for tract,wedge,wedgePop,r= 389 1 223122.780881027 1.9029\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 392 2.0 2 90.0 0.2349 216559.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 392 3.0 2 90.0 0.2127 216559.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 392 4.0 2 90.0 0.1926 216559.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 398 6.0 1 41.4 0.5534 284289.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 398 7.0 1 41.4 0.4977 284289.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 398 8.0 1 41.4 0.4476 284289.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 398 9.0 1 41.4 0.4026 284289.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 398 14.0 1 41.4 0.4015 284289.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 398 19.0 1 41.4 0.401 284289.5\n",
      "7 yoyos for tract,wedge,wedgePop,r= 398 1 284289.46730005625 0.4328\n",
      "I am working on tract number 400 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 402 4.0 0 100.9 0.3399 181689.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 402 5.0 0 100.9 0.3515 181689.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 402 6.0 0 100.9 0.3636 181689.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 402 7.0 0 100.9 0.376 181689.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 402 8.0 0 100.9 0.3889 181689.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 402 9.0 0 100.9 0.4023 181689.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 402 10.0 0 100.9 0.4161 181689.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 411 11.0 0 98.7 0.2946 174647.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 411 12.0 0 98.7 0.3137 174647.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 411 13.0 0 98.7 0.3341 174647.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 411 14.0 0 98.7 0.3558 174647.0\n",
      "I am working on tract number 420 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 433 7.0 0 86.3 0.4317 195902.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 433 8.0 0 86.3 0.422 195902.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 433 9.0 0 86.3 0.4125 195902.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 433 10.0 0 86.3 0.4033 195902.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 433 11.0 0 86.3 0.3942 195902.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 433 12.0 0 86.3 0.3854 195902.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 433 13.0 0 86.3 0.3767 195902.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 433 14.0 0 86.3 0.3683 195902.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 433 15.0 0 86.3 0.36 195902.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 433 16.0 0 86.3 0.3519 195902.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 433 17.0 0 86.3 0.344 195902.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 433 18.0 0 86.3 0.3363 195902.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 433 19.0 0 86.3 0.3288 195902.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 433 20.0 0 86.3 0.3214 195902.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 433 21.0 0 86.3 0.3142 195902.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 433 22.0 0 86.3 0.3072 195902.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 433 23.0 0 86.3 0.3003 195902.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 433 24.0 0 86.3 0.2935 195902.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 433 25.0 0 86.3 0.2869 195902.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 433 26.0 0 86.3 0.2805 195902.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 438 3.0 0 90.0 0.2109 93092.7\n",
      "I am working on tract number 440 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 445 3 545143.6441119956 1.0538\n",
      "8 yoyos for tract,wedge,wedgePop,r= 445 3 92921.53132803115 0.5269\n",
      "9 yoyos for tract,wedge,wedgePop,r= 445 3 545132.7437481806 1.0537\n",
      "9 yoyos for tract,wedge,wedgePop,r= 445 3 489452.77200549614 0.7903\n",
      "9 yoyos for tract,wedge,wedgePop,r= 445 3 304289.53516999225 0.6586\n",
      "10 yoyos for tract,wedge,wedgePop,r= 445 3 173232.62109075137 0.5927\n",
      "11 yoyos for tract,wedge,wedgePop,r= 445 3 263347.86755555903 0.6257\n",
      "11 yoyos for tract,wedge,wedgePop,r= 445 3 224322.99853745094 0.6092\n",
      "11 yoyos for tract,wedge,wedgePop,r= 445 3 199993.6089802774 0.601\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 455 7.0 2 452.4 0.2092 48344.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 455 8.0 2 452.4 0.5176 48344.1\n",
      "I am working on tract number 460 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 460 14.0 3 90.0 0.5762 86838.9\n",
      "7 yoyos for tract,wedge,wedgePop,r= 460 3 829951.7042462474 0.9906\n",
      "8 yoyos for tract,wedge,wedgePop,r= 460 3 86838.85333973577 0.4953\n",
      "9 yoyos for tract,wedge,wedgePop,r= 460 3 1667207.0425137156 1.4223\n",
      "9 yoyos for tract,wedge,wedgePop,r= 460 3 718358.307134347 0.9588\n",
      "10 yoyos for tract,wedge,wedgePop,r= 460 3 103986.43770296208 0.727\n",
      "11 yoyos for tract,wedge,wedgePop,r= 460 3 338421.3609900509 0.8429\n",
      "12 yoyos for tract,wedge,wedgePop,r= 460 3 169832.70599497217 0.785\n",
      "13 yoyos for tract,wedge,wedgePop,r= 460 3 255460.27086760406 0.814\n",
      "13 yoyos for tract,wedge,wedgePop,r= 460 3 206851.67876334576 0.7995\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 463 3.0 3 90.0 0.279 220243.7\n",
      "I am working on tract number 480 of 9129 tracts\n",
      "I am working on tract number 500 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 508 8.0 3 90.0 0.8192 157666.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 508 9.0 3 90.0 0.9396 157666.5\n",
      "I am working on tract number 520 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 520 2 3292986.651747695 0.9067\n",
      "8 yoyos for tract,wedge,wedgePop,r= 520 2 32547.311093502212 0.4534\n",
      "9 yoyos for tract,wedge,wedgePop,r= 520 2 10461675.16631147 1.3573\n",
      "9 yoyos for tract,wedge,wedgePop,r= 520 2 3269306.5960706836 0.9053\n",
      "10 yoyos for tract,wedge,wedgePop,r= 520 2 117105.42725724867 0.6793\n",
      "11 yoyos for tract,wedge,wedgePop,r= 520 2 889919.1882368729 0.7923\n",
      "11 yoyos for tract,wedge,wedgePop,r= 520 2 344216.6026075025 0.7358\n",
      "11 yoyos for tract,wedge,wedgePop,r= 520 2 207573.79377849566 0.7076\n",
      "12 yoyos for tract,wedge,wedgePop,r= 520 2 158169.787611565 0.6935\n",
      "12 yoyos for tract,wedge,wedgePop,r= 520 2 183839.99391713823 0.7005\n",
      "13 yoyos for tract,wedge,wedgePop,r= 520 2 195680.45076402175 0.7041\n",
      "need to widen edge circle beyond 0.0009505587946031149 for tract (x,y)=( -122.11452044861478 37.68764616134602\n",
      "need to widen edge circle beyond 0.0010456146740634264 for tract (x,y)=( -122.11452044861478 37.68764616134602\n",
      "need to widen edge circle beyond 0.0011501761414697692 for tract (x,y)=( -122.11452044861478 37.68764616134602\n",
      "need to widen edge circle beyond 0.0012651937556167462 for tract (x,y)=( -122.11452044861478 37.68764616134602\n",
      "need to widen edge circle beyond 0.001391713131178421 for tract (x,y)=( -122.11452044861478 37.68764616134602\n",
      "need to widen edge circle beyond 0.0015308844442962631 for tract (x,y)=( -122.11452044861478 37.68764616134602\n",
      "need to widen edge circle beyond 0.0016839728887258895 for tract (x,y)=( -122.11452044861478 37.68764616134602\n",
      "need to widen edge circle beyond 0.0018523701775984786 for tract (x,y)=( -122.11452044861478 37.68764616134602\n",
      "need to widen edge circle beyond 0.0020376071953583266 for tract (x,y)=( -122.11452044861478 37.68764616134602\n",
      "need to widen edge circle beyond 0.0022413679148941593 for tract (x,y)=( -122.11452044861478 37.68764616134602\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "7 yoyos for tract,wedge,wedgePop,r= 535 2 451757.3838284755 0.608\n",
      "8 yoyos for tract,wedge,wedgePop,r= 535 2 77037.3922459209 0.304\n",
      "9 yoyos for tract,wedge,wedgePop,r= 535 2 532642.3814064569 0.6799\n",
      "9 yoyos for tract,wedge,wedgePop,r= 535 2 418758.470682845 0.492\n",
      "9 yoyos for tract,wedge,wedgePop,r= 535 2 232389.97933248206 0.398\n",
      "10 yoyos for tract,wedge,wedgePop,r= 535 2 101003.97231891484 0.351\n",
      "10 yoyos for tract,wedge,wedgePop,r= 535 2 153887.30765974426 0.3745\n",
      "7 yoyos for tract,wedge,wedgePop,r= 537 3 1090794.046139786 0.6876\n",
      "7 yoyos for tract,wedge,wedgePop,r= 537 3 868565.0577806295 0.3438\n",
      "8 yoyos for tract,wedge,wedgePop,r= 537 3 95826.34587652795 0.1719\n",
      "9 yoyos for tract,wedge,wedgePop,r= 537 3 621089.2983129001 0.2984\n",
      "10 yoyos for tract,wedge,wedgePop,r= 537 3 160056.60656062682 0.2351\n",
      "11 yoyos for tract,wedge,wedgePop,r= 537 3 320525.89243980916 0.2668\n",
      "11 yoyos for tract,wedge,wedgePop,r= 537 3 217830.2146561942 0.2509\n",
      "12 yoyos for tract,wedge,wedgePop,r= 537 3 183204.7368327621 0.243\n",
      "13 yoyos for tract,wedge,wedgePop,r= 537 3 200267.4543669356 0.247\n",
      "I am working on tract number 540 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 544 2.0 2 90.0 0.4458 315780.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 544 3.0 2 90.0 0.2959 315780.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 556 3.0 2 90.0 0.4823 163929.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 556 4.0 2 90.0 0.5379 163929.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 556 5.0 2 90.0 0.5999 163929.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 557 3.0 3 90.0 0.3001 238883.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 557 4.0 3 90.0 0.2515 238883.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 558 3.0 3 90.0 0.2695 210409.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 559 7.0 0 142.0 0.9275 80690.9\n",
      "I am working on tract number 560 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 562 9.0 0 105.9 1.1961 184821.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 571 3.0 1 90.0 0.4306 149789.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 571 4.0 1 90.0 0.5123 149789.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 571 5.0 1 90.0 0.6095 149789.7\n",
      "I am working on tract number 580 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 588 5.0 1 90.0 0.6515 224399.2\n",
      "7 yoyos for tract,wedge,wedgePop,r= 588 1 209772.09974044465 0.5613\n",
      "8 yoyos for tract,wedge,wedgePop,r= 588 1 60708.62691363922 0.2807\n",
      "9 yoyos for tract,wedge,wedgePop,r= 588 1 221573.9506036845 0.5836\n",
      "10 yoyos for tract,wedge,wedgePop,r= 588 1 91029.78528077697 0.4321\n",
      "10 yoyos for tract,wedge,wedgePop,r= 588 1 136513.5888232428 0.5079\n",
      "7 yoyos for tract,wedge,wedgePop,r= 599 3 200956.49056930872 1.7563\n",
      "8 yoyos for tract,wedge,wedgePop,r= 599 3 122261.42972915777 0.8781\n",
      "9 yoyos for tract,wedge,wedgePop,r= 599 3 201041.55792230455 1.7628\n",
      "10 yoyos for tract,wedge,wedgePop,r= 599 3 138679.96671654732 1.3205\n",
      "10 yoyos for tract,wedge,wedgePop,r= 599 3 174808.37731300676 1.5416\n",
      "11 yoyos for tract,wedge,wedgePop,r= 599 3 199102.95602982328 1.6522\n",
      "I am working on tract number 600 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 616 12.0 0 90.0 0.1758 77857.3\n",
      "I am working on tract number 620 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 624 1 336089.6249342017 0.9726\n",
      "8 yoyos for tract,wedge,wedgePop,r= 624 1 69749.25489412388 0.4863\n",
      "9 yoyos for tract,wedge,wedgePop,r= 624 1 329485.57137180027 0.8964\n",
      "9 yoyos for tract,wedge,wedgePop,r= 624 1 298169.6274003515 0.6913\n",
      "10 yoyos for tract,wedge,wedgePop,r= 624 1 117616.34462150867 0.5888\n",
      "11 yoyos for tract,wedge,wedgePop,r= 624 1 194879.25536457496 0.6401\n",
      "12 yoyos for tract,wedge,wedgePop,r= 624 1 148954.3273491197 0.6144\n",
      "12 yoyos for tract,wedge,wedgePop,r= 624 1 171194.97646237927 0.6273\n",
      "12 yoyos for tract,wedge,wedgePop,r= 624 1 183863.85584923756 0.6337\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 627 5.0 3 90.0 0.6868 180847.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 627 6.0 3 90.0 0.7128 180847.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 627 7.0 3 90.0 0.7398 180847.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 627 8.0 3 90.0 0.7678 180847.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 627 9.0 3 90.0 0.7969 180847.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 627 15.0 3 90.0 0.7521 180847.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 627 16.0 3 90.0 0.7805 180847.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 627 17.0 3 90.0 0.81 180847.6\n",
      "I am working on tract number 640 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 642 3.0 3 36.9 0.5558 945798.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 652 2.0 2 90.0 0.2444 75906.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 652 5.0 2 452.4 0.1937 131558.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 652 6.0 2 452.4 0.2525 131558.1\n",
      "I am working on tract number 660 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 661 1 295212.20931231714 2.8049\n",
      "8 yoyos for tract,wedge,wedgePop,r= 661 1 118222.65933017983 1.4024\n",
      "9 yoyos for tract,wedge,wedgePop,r= 661 1 307650.78800099273 2.9584\n",
      "9 yoyos for tract,wedge,wedgePop,r= 661 1 282983.9868759692 2.1804\n",
      "10 yoyos for tract,wedge,wedgePop,r= 661 1 132212.2915475347 1.7914\n",
      "11 yoyos for tract,wedge,wedgePop,r= 661 1 234823.10401377827 1.9859\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 662 3.0 0 96.8 0.7537 318003.3\n",
      "7 yoyos for tract,wedge,wedgePop,r= 663 2 342413.5242979555 1.4199\n",
      "8 yoyos for tract,wedge,wedgePop,r= 663 2 80374.69117642325 0.71\n",
      "9 yoyos for tract,wedge,wedgePop,r= 663 2 482693.0690951389 1.9188\n",
      "9 yoyos for tract,wedge,wedgePop,r= 663 2 300197.7970777119 1.3144\n",
      "10 yoyos for tract,wedge,wedgePop,r= 663 2 86442.16583139752 1.0122\n",
      "10 yoyos for tract,wedge,wedgePop,r= 663 2 147007.76577668078 1.1633\n",
      "11 yoyos for tract,wedge,wedgePop,r= 663 2 206649.26497452773 1.2388\n",
      "12 yoyos for tract,wedge,wedgePop,r= 663 2 171458.79621109465 1.2011\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 676 3.0 3 -43.1 0.5512 744052.0\n",
      "7 yoyos for tract,wedge,wedgePop,r= 678 0 465719.3794184885 1.9146\n",
      "8 yoyos for tract,wedge,wedgePop,r= 678 0 56298.152080247935 0.9573\n",
      "9 yoyos for tract,wedge,wedgePop,r= 678 0 346127.1556584826 1.773\n",
      "9 yoyos for tract,wedge,wedgePop,r= 678 0 295739.8832849257 1.3651\n",
      "10 yoyos for tract,wedge,wedgePop,r= 678 0 135677.69488334266 1.1612\n",
      "11 yoyos for tract,wedge,wedgePop,r= 678 0 252093.02990205184 1.2632\n",
      "12 yoyos for tract,wedge,wedgePop,r= 678 0 185142.20645254932 1.2122\n",
      "13 yoyos for tract,wedge,wedgePop,r= 678 0 215770.5777494074 1.2377\n",
      "13 yoyos for tract,wedge,wedgePop,r= 678 0 200411.58257133045 1.2249\n",
      "I am working on tract number 680 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 694 2.0 3 90.0 0.1712 28853.7\n",
      "I am working on tract number 700 of 9129 tracts\n",
      "I am working on tract number 720 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 732 1 1457505.1397236092 0.5619\n",
      "7 yoyos for tract,wedge,wedgePop,r= 732 1 434066.29548800655 0.2809\n",
      "8 yoyos for tract,wedge,wedgePop,r= 732 1 56288.44908461918 0.1405\n",
      "9 yoyos for tract,wedge,wedgePop,r= 732 1 423981.5769269708 0.2795\n",
      "10 yoyos for tract,wedge,wedgePop,r= 732 1 70537.4671492101 0.21\n",
      "10 yoyos for tract,wedge,wedgePop,r= 732 1 137121.9697553686 0.2447\n",
      "11 yoyos for tract,wedge,wedgePop,r= 732 1 282906.92427684524 0.2621\n",
      "12 yoyos for tract,wedge,wedgePop,r= 732 1 198400.33837963408 0.2534\n",
      "loop31.0, tr732,wedgePops776948.4, 217845.8, 235321.7, 217760.9, 106020.0, Overedge?0, 0, 0, 1, ,Satisfied?1010,yoyo?01200 \n",
      "   targetWP, latest drx4 are tWP,dr, 218110.1,0.0004, 218110.1,0.0043, 218110.1,0.0006, 218110.1,0.9104\n",
      "13 yoyos for tract,wedge,wedgePop,r= 732 1 235321.6793862054 0.2578\n",
      "loop32.0, tr732,wedgePops757602.44, 217845.8, 215975.7, 217760.9, 106020.0, Overedge?0, 0, 0, 1, ,Satisfied?1010,yoyo?01300 \n",
      "   targetWP, latest drx4 are tWP,dr, 218110.1,0.0004, 218110.1,-0.0022, 218110.1,0.0006, 218110.1,0.9104\n",
      "I am working on tract number 740 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 744 4.0 2 90.0 0.3366 170229.2\n",
      "7 yoyos for tract,wedge,wedgePop,r= 755 1 307361.78568124713 3.1642\n",
      "8 yoyos for tract,wedge,wedgePop,r= 755 1 132311.45785663137 1.5821\n",
      "9 yoyos for tract,wedge,wedgePop,r= 755 1 304674.8737747796 2.8252\n",
      "9 yoyos for tract,wedge,wedgePop,r= 755 1 291550.685029495 2.2036\n",
      "9 yoyos for tract,wedge,wedgePop,r= 755 1 238729.5943587086 1.8929\n",
      "10 yoyos for tract,wedge,wedgePop,r= 755 1 156013.5264911989 1.7375\n",
      "11 yoyos for tract,wedge,wedgePop,r= 755 1 210487.2061283989 1.8152\n",
      "12 yoyos for tract,wedge,wedgePop,r= 755 1 178962.30332740935 1.7763\n",
      "7 yoyos for tract,wedge,wedgePop,r= 756 1 265547.1898076533 1.8529\n",
      "8 yoyos for tract,wedge,wedgePop,r= 756 1 90537.30975105971 0.9265\n",
      "9 yoyos for tract,wedge,wedgePop,r= 756 1 271981.11881775875 2.1963\n",
      "10 yoyos for tract,wedge,wedgePop,r= 756 1 113539.43350178859 1.5614\n",
      "11 yoyos for tract,wedge,wedgePop,r= 756 1 269178.37632755813 1.8789\n",
      "11 yoyos for tract,wedge,wedgePop,r= 756 1 249780.45384904748 1.7201\n",
      "12 yoyos for tract,wedge,wedgePop,r= 756 1 176511.97813322156 1.6408\n",
      "loop31.0, tr756,wedgePops781979.54, 189761.1, 212730.7, 189738.6, 189749.1, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?01200 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0005, 190087.6,0.0397, 190087.6,0.003, 190087.6,0.0005\n",
      "13 yoyos for tract,wedge,wedgePop,r= 756 1 212730.70534345528 1.6804\n",
      "loop32.0, tr756,wedgePops762274.48, 189761.1, 193025.6, 189738.6, 189749.1, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?01300 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0005, 190087.6,-0.0198, 190087.6,0.003, 190087.6,0.0005\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 757 7.0 0 83.4 0.3057 240784.0\n",
      "I am working on tract number 760 of 9129 tracts\n",
      "I am working on tract number 780 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 790 2.0 1 90.0 0.2145 96150.5\n",
      "I am working on tract number 800 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 801 1 271852.05838393886 1.393\n",
      "8 yoyos for tract,wedge,wedgePop,r= 801 1 94397.36470815333 0.6965\n",
      "9 yoyos for tract,wedge,wedgePop,r= 801 1 306549.24391793227 1.9895\n",
      "9 yoyos for tract,wedge,wedgePop,r= 801 1 265939.31235912506 1.343\n",
      "10 yoyos for tract,wedge,wedgePop,r= 801 1 100172.86083964299 1.0198\n",
      "10 yoyos for tract,wedge,wedgePop,r= 801 1 124681.4783722593 1.1814\n",
      "11 yoyos for tract,wedge,wedgePop,r= 801 1 194293.91570189898 1.2622\n",
      "12 yoyos for tract,wedge,wedgePop,r= 801 1 151258.23261865173 1.2218\n",
      "12 yoyos for tract,wedge,wedgePop,r= 801 1 172909.24866298065 1.242\n",
      "loop31.0, tr801,wedgePops754547.4, 190500.3, 183684.6, 189919.6, 190442.8, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?11221 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,-0.001, 190087.6,0.0101, 190087.6,0.0002, 190087.6,-0.0005\n",
      "12 yoyos for tract,wedge,wedgePop,r= 801 1 183684.61475867932 1.2521\n",
      "loop32.0, tr801,wedgePops759965.41, 190500.3, 189102.6, 189919.6, 190442.8, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?11221 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,-0.001, 190087.6,0.0051, 190087.6,0.0002, 190087.6,-0.0005\n",
      "I am working on tract number 820 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 824 5.0 1 90.0 0.7128 152136.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 4.0 1 90.0 0.6018 184945.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 5.0 1 90.0 0.6142 184945.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 6.0 1 90.0 0.627 184945.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 7.0 1 90.0 0.6399 184945.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 8.0 1 90.0 0.6532 184945.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 9.0 1 90.0 0.6667 184945.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 10.0 1 90.0 0.6805 184945.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 11.0 1 90.0 0.6946 184945.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 12.0 1 90.0 0.709 184945.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 13.0 1 90.0 0.7237 184945.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 14.0 1 90.0 0.7387 184945.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 15.0 1 90.0 0.754 184945.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 16.0 1 90.0 0.7696 184945.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 17.0 1 90.0 0.7855 184945.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 23.0 1 90.0 0.707 184945.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 24.0 1 90.0 0.7216 184945.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 25.0 1 90.0 0.7365 184945.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 26.0 1 90.0 0.7518 184945.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 27.0 1 90.0 0.7674 184945.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 28.0 1 90.0 0.7833 184945.2\n",
      "loop31.0, tr826,wedgePops811501.89, 189838.6, 241710.4, 189788.5, 190164.4, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0303 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0008, 190087.6,-0.3215, 190087.6,0.0004, 190087.6,-0.0002\n",
      "loop32.0, tr826,wedgePops713291.16, 189838.6, 143499.7, 189788.5, 190164.4, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0303 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0008, 190087.6,-0.4623, 190087.6,0.0004, 190087.6,-0.0002\n",
      "loop33.0, tr826,wedgePops754736.73, 189838.6, 184945.2, 189788.5, 190164.4, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0403 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0008, 190087.6,0.2059, 190087.6,0.0004, 190087.6,-0.0002\n",
      "loop34.0, tr826,wedgePops754736.73, 189838.6, 184945.2, 189788.5, 190164.4, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0403 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0008, 190087.6,0.017, 190087.6,0.0004, 190087.6,-0.0002\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 34.0 1 90.0 0.6853 184945.2\n",
      "loop35.0, tr826,wedgePops754736.73, 189838.6, 184945.2, 189788.5, 190164.4, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0403 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0008, 190087.6,0.0142, 190087.6,0.0004, 190087.6,-0.0002\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 35.0 1 90.0 0.6994 184945.2\n",
      "loop36.0, tr826,wedgePops754736.73, 189838.6, 184945.2, 189788.5, 190164.4, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0403 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0008, 190087.6,0.0145, 190087.6,0.0004, 190087.6,-0.0002\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 36.0 1 90.0 0.7139 184945.2\n",
      "loop37.0, tr826,wedgePops754736.73, 189838.6, 184945.2, 189788.5, 190164.4, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0403 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0008, 190087.6,0.0148, 190087.6,0.0004, 190087.6,-0.0002\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 37.0 1 90.0 0.7287 184945.2\n",
      "loop38.0, tr826,wedgePops754736.73, 189838.6, 184945.2, 189788.5, 190164.4, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0403 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0008, 190087.6,0.0151, 190087.6,0.0004, 190087.6,-0.0002\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 38.0 1 90.0 0.7438 184945.2\n",
      "loop39.0, tr826,wedgePops754736.73, 189838.6, 184945.2, 189788.5, 190164.4, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0403 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0008, 190087.6,0.0154, 190087.6,0.0004, 190087.6,-0.0002\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 0 0.1655 188851.3442 189838.5932 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 1 0.75921 184945.2264 184945.2264 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 2 0.11266 188665.9307 189788.5159 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 3 0.25398 191113.0147 190164.3956 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 826 39.0 1 90.0 0.7592 184945.2\n",
      "loop40.0, tr826,wedgePops754736.73, 189838.6, 184945.2, 189788.5, 190164.4, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0403 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0008, 190087.6,0.0157, 190087.6,0.0004, 190087.6,-0.0002\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 0 0.1655 188851.3442 189838.5932 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 1 0.77494 184945.2264 184945.2264 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 2 0.11266 188665.9307 189788.5159 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 3 0.25398 191113.0147 190164.3956 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I looped 40 times on tract 826, giving up w pop 754736.731194434\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 7.0 1 37.7 0.5847 181542.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 8.0 1 37.7 0.6051 181542.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 9.0 1 37.7 0.6262 181542.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 10.0 1 37.7 0.648 181542.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 11.0 1 37.7 0.6706 181542.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 12.0 1 37.7 0.694 181542.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 17.0 1 37.7 0.5162 181542.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 18.0 1 37.7 0.5342 181542.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 19.0 1 37.7 0.5529 181542.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 20.0 1 37.7 0.5722 181542.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 21.0 1 37.7 0.5921 181542.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 22.0 1 37.7 0.6128 181542.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 23.0 1 37.7 0.6342 181542.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 24.0 1 37.7 0.6563 181542.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 25.0 1 37.7 0.6792 181542.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 30.0 1 37.7 0.523 181542.3\n",
      "loop31.0, tr838,wedgePops751015.77, 189689.4, 181542.3, 189992.3, 189791.8, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0402 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0023, 190087.6,0.0183, 190087.6,0.0002, 190087.6,0.0004\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 31.0 1 37.7 0.5412 181542.3\n",
      "loop32.0, tr838,wedgePops751015.77, 189689.4, 181542.3, 189992.3, 189791.8, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0402 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0023, 190087.6,0.0189, 190087.6,0.0002, 190087.6,0.0004\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 32.0 1 37.7 0.5601 181542.3\n",
      "loop33.0, tr838,wedgePops751015.77, 189689.4, 181542.3, 189992.3, 189791.8, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0402 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0023, 190087.6,0.0195, 190087.6,0.0002, 190087.6,0.0004\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 33.0 1 37.7 0.5797 181542.3\n",
      "loop34.0, tr838,wedgePops751015.77, 189689.4, 181542.3, 189992.3, 189791.8, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0402 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0023, 190087.6,0.0202, 190087.6,0.0002, 190087.6,0.0004\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 34.0 1 37.7 0.5999 181542.3\n",
      "loop35.0, tr838,wedgePops751015.77, 189689.4, 181542.3, 189992.3, 189791.8, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0402 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0023, 190087.6,0.0209, 190087.6,0.0002, 190087.6,0.0004\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 35.0 1 37.7 0.6208 181542.3\n",
      "loop36.0, tr838,wedgePops751015.77, 189689.4, 181542.3, 189992.3, 189791.8, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0402 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0023, 190087.6,0.0217, 190087.6,0.0002, 190087.6,0.0004\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 36.0 1 37.7 0.6425 181542.3\n",
      "loop37.0, tr838,wedgePops751015.77, 189689.4, 181542.3, 189992.3, 189791.8, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0402 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0023, 190087.6,0.0224, 190087.6,0.0002, 190087.6,0.0004\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 37.0 1 37.7 0.6649 181542.3\n",
      "loop38.0, tr838,wedgePops751015.77, 189689.4, 181542.3, 189992.3, 189791.8, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0402 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0023, 190087.6,0.0232, 190087.6,0.0002, 190087.6,0.0004\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 838 38.0 1 37.7 0.6881 181542.3\n",
      "loop39.0, tr838,wedgePops751166.53, 189689.4, 181693.0, 189992.3, 189791.8, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0402 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0023, 190087.6,0.024, 190087.6,0.0002, 190087.6,0.0004\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 0 0.29882 188493.2208 189689.3584 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 1 0.71212 181542.2814 181693.0393 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 2 0.19431 189606.437 189992.3105 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 3 0.28119 188747.0696 189791.8213 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loop40.0, tr838,wedgePops870723.36, 189689.4, 301249.9, 189992.3, 189791.8, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0402 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0023, 190087.6,0.6643, 190087.6,0.0002, 190087.6,0.0004\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 0 0.29882 188493.2208 189689.3584 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 1 1.37643 181693.0393 301249.8715 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 2 0.19431 189606.437 189992.3105 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 3 0.28119 188747.0696 189791.8213 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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FRNKcEr2ISJpTohcRSXNK9CIiaU6JXkQkzSVSSrCFmc03s8VmttTMxsasG25m7wfvT6ym/fnB+iVmdr+ZtUjmAYiISM2yEtimCOjj7mvNLAK8ZmbPALlAf6CHuxeZ2XZVG5pZJ2AEsKe7rzez2UTLD96VtCMQEZEa1ZroPVprcG2wGAkeDgwFJrh7UbDdyho+I9fMSoCWwNf1DVpERBKX0Bi9mWWa2SJgJdHi4POAbkBvM5tnZq+Y2X5V27n7V8D1wBfAN8AP7v58NZ8xxMwKzKygsLBwCw9HRESqSijRu3uZu/cEOgO9zKw70Z761sD+wChgtplZbDsz25ro8M6OQEeglZmdUs1nzHD3fHfPz8vL29LjERGRKuo068bdVwMvA4cBK4BHPWo+UA60r9KkL/Cpuxe6ewnwKHBAfYMWEZHEJTLrJs/M2gWvc4km7+XA40Cf4P1uQDawqkrzL4D9zaxl0Ns/BFiWrOBFRKR2icy66QDMMrNMov8wzHb3OWaWDdxhZkuAYmCQu7uZdQRmuns/d59nZg8DbwGlwNvAjNQcioiIxGPRSTWNS35+vhcUFIQdhohIk2FmC909P946XRkrIpLmlOhFRNKcEr2ISJpL5MdYEWki3J2i4hKKS0ooKiqmuKSEDcFzdctFRcUUVVmO3W7nn3fhtBP6k5GhfmFTpUQvkgTl5eW1Jth4CXWT5eISiotL2FBcTHFxCUUxz0VVluNvF/38ZIhkZZGTk01WViarf1jDa/Pf5sbxF9Omdauk7F8alhK9NGkVCXZLkmLFtjX1aqtNzsXFFBVtbFtSWpqU48mORMjJjpCdHSEnO5vs7AgtgueK5TatW5ETs7z5dpHofnKyyQmeq1vOjkRoUWU5JzuySe/9roee5Mrr/85Rp53HnZPH0rVzx6QcqzQcTa+ULVJWVlbNsEAJxSUVSTD6XGMvtrreb2XCLqG4IiHHSdjJSrA1J86Nz9FEGSE7kh08x0mUCSbUqsvZkaxGOzzy2oK3OXP01QDcOuFyfrPfPiFHJFXVNL1Sib4JWfXd97Rr25bikuIgodZhWKBqQt2sB7wxocbrEVftKZeWldX7eMxs8wS7SaKM1NzzrNguNhHX1tOt3Gbj+uxIhCq3aZI4PlvxNadeMIaPP/+ScSPPZvBxR4UdksSoKdFr6KaJWPzeB/QbOCwp+4om2KpJMZoEW2RHE2jrlrnktNuq2gRaXdvNesA1LEeyspRgm5CunTvy5B1TGH7FdVx23U0s/+gzxo0cSnYkEnZoUgsl+iagrKyMSyZMA+CEI//ALl27bNLbreswQVZmphKsbJE2rVtx+/VjmDj9Lm6660E++vQLZky8gm3abRV2aFIDJfom4OZZs1n83gdMHXsRxx7RN+xwpJnLzMzkkmGns9vOXRk5fjL9Bg7jzsnj2GOXHcMOTarROH/5kUqL3/uASbfezZG//y1/7ndI2OGIVDrm8EN49LbJlJSUctSp5/Lsy6+HHZJUQ4m+EVu3fj3DLp9AXvutmXDJCA23SKPTc6/dePrum9htp59z+sixTJl5H41xgkdzp0TfiI29YQaffvkVU8deRLu2bcIORySuHfK25aFbr+eYw/vwt1tmcfal17B+w4aww5IYSvSN1POvvsm9jz7NWaccy4H5PcMOR6RGuS1ymDbuYi4bfgZP/fNVjj7jAr7678qww5JAIhWmWpjZfDNbbGZLzWxszLrhZvZ+8P7Eatq3M7OHzWy5mS0zs18n8wDSUeH/vmfk+Mns1W1nRg0dFHY4IgkxM84edDx33TCOT7/8miMGDafgnffCDktIrEdfBPRx972BnsBhZra/mf2OaOHvHu6+F3B9Ne2nAs+6++7A3qiUYI3cnQvGTeKndeu56erR5GRnhx2SSJ30/c2veOrOqbTKzeW4M0cxe87zYYfU7NWa6IPi32uDxUjwcGAoMMHdi4LtNvueZmZtgYOA24NtioMC41KNWQ89xb9en8/lI/5Ct51+HnY4Iluk204/56m7prFfz704/6rrGTdlBmVJuJpatkxCY/Rmlmlmi4CVwAvuPg/oBvQ2s3lm9oqZ7Ren6U5AIXCnmb1tZjPNLO7t78xsiJkVmFlBYWHhlh1NE/fhp18wfuoMfndAPoOP1+Xl0rRt064t9914Daed0J9b732YQedfwQ9r1tbeUJIuoUTv7mXu3hPoDPQys+5EL7baGtgfGAXMts3n/2UB+wLT3X0f4CdgdDWfMcPd8909Py8vb4sOpikrLilh2OUTaJmby+QrR2oqpaSFSFYW40edw8TLzuPf897myMEj+PjzFWGH1ezUadZNMOzyMnAYsAJ4NBjamQ+UA+2rNFkBrAi+AQA8TDTxSxV/mz6LJe9/xKQrLmC79tuEHY5IUp18dD8enH4d3/+whiMHj+CV/+imhQ0pkVk3eWbWLnidC/QFlgOPA32C97sB2cCq2Lbu/l/gSzPbLXjrEEA/w1fxRsFipt/zECcf3Y9Df6tJSZKe9t+3B3PvvpGOO2zHKSMuZ+b9j+niqgaSSI++A/CSmb0DLCA6Rj8HuAPYycyWAA8Ag9zdzayjmc2NaT8cuC9o3xO4JqlH0MSt/nENI8ZcR9cuHbnqgjPDDkckpbp03IEnbr+BP/z214yZNJ2R4ydTVFwcdlhpT/ejD5G7c85l1/L0i//miTum0HOv3WpvJJIGysvLmTTjHqbMvI/99t6L2yZeSd62W4cdVpNW0/3odWVsiB595kWeeP5lLhgyQElempWMjAxGnTWI6ddexrvLP6LfwGEsef/jsMNKW0r0Ifny6/9y2XU3sd/eezFs8AlhhyMSiqN+/1sev30yjvOn089jzj9fDTuktKREH4KysjLOHTMRB6aNu4jMzMywQxIJzS9235Vn7r6ZPbvtzJmjr2bSrXdTXl4edlhpRYk+BDfPms28t5fw14uG8bNOHcIORyR0edtuzUO3TOT4Iw9l8m33cuboq1m3fn3YYaUNJfoGVlFI5CgVEhHZRE52NpOvvJAx55/Jsy+/Qf/Tz2fFN9+GHVZaUKJvQLGFRK5VIRGRzZgZQ07+M/dMvZoVX39Lv4HDmL9oSdhhNXlK9A1IhUREEnPwr/N56q5pbNWmDcefdRH/ePyZsENq0pToG8jzr6iQiEhd7NK1C0/dNZUD8vdm1NU3cOX1f6e0VHfA3BJK9A1g5arvuFCFRETqrF3bNtw95WqGnPxnbn/gcU4ZcSnf//Bj2GE1OUr0KebuXDhuEuvWq5CIyJbIyspkzPlnMvnKC5n39hL+OHgEH376RdhhNSlK9Ck266Gn+NcbC1RIRKSeTjjqD8y+ZSJrf1rHkYNH8OJr88MOqclQok+hDz75nPFTZ9DngP1USEQkCfbbey/m3n0TP+vUgUHnX8H0u2frDpgJUKJPkdhCIpOuvFBTKUWSpNMO2/H47ZM54pDeXD1tJueO+RsbinQHzJoo0afI36bPYukHH6uQiEgKtMzN5ZZrL2PkWQN5ZO4/OfbMkXy76n9hh9VoKdGngAqJiKSemXH+Gadw28QrWf7Rp/QbOJzF730QdliNkhJ9klUUEtmxSycVEhFpAP36/IYn7phCVmYmx/zlAh5/9qWwQ2p0Eikl2MLM5pvZYjNbamZjY9YNN7P3g/cn1rCPTDN728zmJCvwxsjdueTaaRSu+p6brh5Ny9zcsEMSaRb26rYzc+++kb337MY5l1/LhJvv1B0wY2QlsE0R0Mfd15pZBHjNzJ4BcoH+QA93LzKz7WrYx7nAMqBtvSNuxB595kWefOEVLho6mL337BZ2OCLNyrZbt+OBv1/H5RNv4sY77+f9jz/jxvEX07pVy7BDC12tPXqPWhssRoKHA0OBCe5eFGy3Ml57M+sMHAHMTErEjVRFIZFePburkIhISLIjEa679DzGjzybF1+fx1GnnsvnK74JO6zQJTRGHwy9LAJWEi0OPg/oBvQ2s3lm9oqZ7VdN8ynARUCN36PMbIiZFZhZQWFhYcIH0BiUlZUx4koVEhFpDMyM0078E/dOu4ZvV33HEYOG80bB4rDDClVCid7dy9y9J9AZ6GVm3YkO+2wN7A+MAmZblcniZvZHYKW7L0zgM2a4e7675+fl5dXxMMJ186zZzF8ULSTSpeMOYYcjIsBBv9qXObOm0X6bdpx0zmhmPfxU2CGFpk6zbtx9NfAycBiwAng0GNqZT7TH3r5KkwOBo8zsM+ABoI+Z3VvPmBsVFRIRabx27NKJJ++cykH7/5JLJ9zI6GunUVJaGnZYDS6RWTd5ZtYueJ0L9AWWA48DfYL3uwHZwKrYtu5+ibt3dveuwInAv9z9lCTGH6qKQiLbtd9GhUREGqm2rVtx1+SxnD3weO55ZA4nnXMJ363+IeywGlQiPfoOwEtm9g6wgOgY/RzgDmAnM1tCtLc+yN3dzDqa2dzUhdx4XDX5Vj798iumjB2lQiIijVhmZiaXjTiDaeMu4q133+OIQcNZ/tGnYYfVYKwx3hAoPz/fCwoKwg6jRs+/8ianXjiGoQOO4/Jz/xJ2OCKSoLeWLOOMkWNZu249N40fnTZXr5vZQnfPj7dOV8ZuARUSEWm69u2+B0/ffRO7dO3CaSOvYtod96f9HTCV6OvI3blg3PWsW7+em/96iQqJiDRBHbZrzyMzJvGnPxzMdX+/k2GXT2D9hqKww0oZJfo6mvXQU7z0RgFXnDuEXXf8WdjhiMgWym2Rw43jR3PJsNN44vmXOeYvF/D1t03rGp5EKdHXQWwhkUHHHRl2OCJST2bGsMEncsekq/j48xUcMXA4C99dFnZYSadEn6Ci4mIVEhFJU4ce9GueunMquS1yOO7MkTz89D/DDimplOgTpEIiIultt527MmfWjfyyx56cO2YiV0+9jbKysrDDSgol+gS8XrCIW+59WIVERNLcNu3a8o+brmXQcUcy/Z6HGHz+lfy49qeww6o3JfparP5xDeeOmahCIiLNRCQri2suHs61o0fw6ry3OHLwCD754quww6oXJfoaqJCISPM18Ng/cv/NE/jf9z9w5OBo0m+qlOhr8MjcaCGRC88cqEIiIs3QAfl7M/fuG9khb1tOGXEptz/wWJO8uEqJvhpffv1fLpsYLSRyzqDjww5HRELys04deOKOKfT9za+48vrpjLr6BopLSsIOq06U6OOoKCRiqJCIiEDrVi2Z+bcxjDjtJO5/4llOGHoxq777PuywEqZEH8dNdz0YLSRysQqJiEhURkYGF599Kn+/5lLeWfYB/QYOZ8n7H4cdVkKU6KtYtPR9Js+4h6N+/1uOOVyFRERkU/0PPZjHZk6mrLycP51+Hk+/+O+wQ6qVEn2MdevXM/yK61RIRERq1GOPbsy9+0Z232VHhlw8nskz7qG8vMay2KFKpMJUCzObb2aLzWypmY2NWTfczN4P3p8Yp20XM3vJzJYF25yb7ANIpopCIlPHXqRCIiJSo+3bb8vDt17PsUf0ZdKMezjrkr+ybv36sMOKKyuBbYqAPu6+1swiwGtm9gyQC/QHerh7kZltF6dtKXChu79lZm2AhWb2gru/l7QjSJLnXn6D+x6by9kDj+eA/L3DDkdEmoAWOdlMuWoUe+y6E3+dNpPPvvyaOyePpdMO8dJheGrt0QfFv9cGi5Hg4cBQYIK7FwXbrYzT9ht3fyt4vQZYBnRKUuxJs3LVd4y8+gb26rYzI88aGHY4ItKEmBlnnXIss24YxxdffcPhA85hwaKlYYe1iYTG6M0s08wWASuJ1oydB3QDepvZPDN7xcz2q2UfXYF9gHn1Czm5VEhERJKhz4G9mDNrGm3btOa4s0bxwBPPhh1SpYQSvbuXuXtPoDPQy8y6Ex322RrYHxgFzLZqfr00s9bAI8B57v5jNdsMMbMCMysoLGy4m//fNftJFRIRkaTYpevPmHPXNH79yx5cOH4yYyZNp7Q0/Dtg1mnWjbuvBl4GDgNWAI8GQzvzgXKgfdU2wbj+I8B97v5oDfue4e757p6fl5dXl7C22AeffM7V025TIRERSZp2bdtwz9S/cvpJRzPz/scYcO5lrP5xTagxJTLrJs/M2gWvc4G+wHLgcaBP8H43IBtYVaWtAbcDy9x9cjIDry8VEhGRVMnKymTchUO5/vLzeXPhO/xx8Ag++uyL0OJJpEffAXjJzN4BFhAdo58D3AHsZGZLgAeAQe7uZtbRzOYGbQ8EBgB9zGxR8OiXguOos8pCIleqkIiIpMZJfzqc2bdM5Mc1azly8Ln86/X5ocRhjfFObPn5+V5QUJCy/b9esIgThl7MyUf347pLG/XUfhFJA1/9dyWDL7iS5R99xmUjzuDMk/+c9FEEM1vo7vnx1jW7K2NjC4mMOX9I2OGISDPQaYfteOL2Gzjs4AMYP2UG54+9ng1FxQ32+c0q0auQiIiEpWVuLrdOuJwLhwzgoTkvcNxZo1i56rsG+exmlehVSEREwpSRkcEFQwYw47orWPbhJ/QbNIx3ln2Q+s9N+Sc0El989Y0KiYhIo3DEIb15/PYpZFgGR59xIU88/3JKP69ZJHoVEhGRxqb7bjsz9+4b+cXuu3D2pddw3d/vTNkdMBO5qVmTd9NdD7Jg8VKmjbtIhUREpM7cnaLiEoqKiykOnuMtF5eUUFRUXPlcVGW5uKSEDZXLJRSXFLNV29aYGdPuuJ+Vq75j0pUXJj3+tE/0FYVE+h96sAqJiDQx5eXltSbY4uISNlRZLoqTfOMl3XjvF5Vsup/iYB/JkJMdITsSIScnu/I5JxKhxx67kh2JsH3etkn5nKrSOtH/tG49w66YwHbtt+Ga0cN19atIgsrKyqr0Pit6o9FeaFHMc9xEWW0vNniuTNglFFck5DgJu6S0NCnHk5MdISc7m+zgOfrY+F5uixy2atsmeK/qtpsuZ2dHaFFlOd52FfvKDl5nRyKh5aC0TvRjb7iVz778mtnTJ6qQiDQJpaVlFJcUBwk1gZ5ndQl1sx7wxoQar0dctadcWlb/G3GZ2eZJMqYXm5MToWWLHLbeqg3ZkQgtYnq5m2yXcNLdmFRjtwszwTYWaZvoVUhEEuXulJaV1Tj2mvjQQUniQwxxEnZZWf1/jIsm2OyYxBmpkmCzad0yl5x2W9XSG900gbbIjiTYi40uR7Kymn2CbSzSMtHHFhIZNXRQ2OFINdydktLSOibUTb/qJ9Qubg+4ZJMecDJmO2RkZEQTXUxCzY5s2vNs27pVLQm1LsMC8ZezMjOVYGUTaZfoqxYSyY5Ewg6p0XF3ikuqJsqax0rjJtRExmKrjuFW2V8y7rWUmZkRf+w0phe7Vds2mwwLtMiJkB3J3tjbjUmWmw0d1LAcu6+sLE3blcYp7RJ9RSGRv140rNEVEqmYolVTYtw8USY2RasyodY6GyGaYJMhKzOz1iS4dbsWm/RqE+md1tyr3XQcVglWpHZplegrC4kc2GuTQiIVU7TqmlA37Ykm3tOtbrpXsqZoRbKyYhJqhJxIduXX/orE2LrlVrV+/U/kh6zqEnN2JKILz0SaiLRK9COvvoENRcW8tWQZPX5/fGXCTtYUrexIpDIpVtfzbNO6Ve0JtU7DAlVmImRHyMhoFhc0i0iSpFWiP+TAXnTpsP0mP25V9kC3aA5s7HhvlhKsiDRJtSZ6M2sBvArkBNs/7O5jgnXDgWFAKfC0u18Up/1hwFQgE5jp7hOSF/6mzj39/1K1axGRJiuRHn0R0Mfd1waFvl8zs2eAXKA/0MPdi8xsu6oNzSwTuBn4PdFi4gvM7El3fy95hyAiIjWpdSzCo9YGi5Hg4cBQYIK7FwXbrYzTvBfwkbt/4u7FRGvL9k9K5CIikpCEBp3NLNPMFgEriRYHnwd0A3qb2Twze8XM9ovTtBPwZczyiuC9eJ8xxMwKzKygsLCwTgchIiLVSyjRu3uZu/cEOgO9zKw70WGfrYH9gVHAbNv8crx4l+fFvULG3We4e7675+fl5SUav4iI1KJO00jcfTXwMnAY0d75o8HQznygHGhfpckKoEvMcmfg6y0NVkRE6q7WRG9meWbWLnidC/QFlgOPA32C97sB2cCqKs0XALua2Y5mlg2cCDyZrOBFRKR2icy66QDMCmbQZACz3X1OkLjvMLMlQDEwyN3dzDoSnUbZz91LzWwY8BzR6ZV3uPvSFB2LiIjEYcm4qVSy5efne0FBQdhhiIg0GWa20N3z465rjInezAqBz1O0+/ZsPsTU3OmcbErnY3M6J5tqjOfj5+4edyZLo0z0qWRmBdX9q9dc6ZxsSudjczonm2pq50M3bxERSXNK9CIiaa45JvoZYQfQCOmcbErnY3M6J5tqUuej2Y3Ri4g0N82xRy8i0qwo0YuIpLm0SfRmdpyZLTWzcjPLj3n/92a20MzeDZ4rbtvQ0syeNrPlQbsaC6KY2c/MbK2ZjUz1sSRDqs5Hde2bglT+jZjZJWb2kZm9b2Z/aIjjqa+6no9g3V/N7EszWxt/r2BmETObFbRfZmaXpPpYkiVV5yTYroeZvRns/92gqFPDcPe0eAB7ALsRvelafsz7+wAdg9fdga+C1y2B3wWvs4F/A4fXsP9HgIeAkWEfa5jno7r2TeGRwnOyJ7CYaBW2HYGPgcywjzfZ5yNY3p/obVHW1rDf/wMeiDmHnwFdwz7ekM9JFvAOsHewvG1D/o2kTc1Yd18GUPVOye7+dsziUqCFmeW4+zrgpWCbYjN7i+jdNTdjZn8CPgF+Sn7kqZGq81FD+6IkH0LSpfBvpD/RxFYEfGpmHxEtuvNm8o8iebbgfBS5+3/itam6a6CVmWURrURXDPyYxNBTJoXn5FDgHXdfHOzvf8mMuzZpM3SToD8Db1dNSsHdOY8EXqzawMxaARcDYxsiwAZW5/ORSPsmbkvOScIFdpqgLflv/DDRTtE3wBfA9e7+XSqCC8mWnJNugJvZc2b2lpltVl87lZpUj97M/gnsEGfVZe7+RC1t9wKuI/ova+z7WcD9wDR3/yRO07HADR6tmbtlgadISOejxvZhC+mcJFxgp6Gl4nwkoBdQBnQkWpzo32b2z5r+nhpSSOckC/gNsB+wDnjRojchq60zlRRNKtG7e98taWdmnYHHgIHu/nGV1TOAD919SjXNfwUca2YTgXZAuZltcPebtiSWZArpfNTWPlQhnZNGW2AnReejNv8HPOvuJcBKM3sdyCc6/Bm6kM7JCuAVd18V7GsusC+1f2tOirQfugm+cj8NXOLur1dZdzWwFXBede3dvbe7d3X3rsAU4JrGkOS3VH3PR03tm6r6nhOixXRONLMcM9sR2BWYn5poUy8J/42/APpYVCuiP1YuT2KIDS4J5+Q5oEcwkysL+C3wXhJDrFlD/eqb6gdwNNF/NYuAb4HngvcvJzpeuCjmsR3RXpcDy2LePyNocxQwLs5nXEXTmXWTkvNRXfuwjzfsvxHgMqKzbd6nhtlbjelR1/MRrJsYtCkPnq+K8zfSmugMtaVEk9mosI817HMSLJ8SnJMlwMSGPC7dAkFEJM2l/dCNiEhzp0QvIpLmlOhFRNKcEr2ISJpTohcRSXNK9CIiaU6JXkQkzf0/3vAgkt1ew5wAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I looped 40 times on tract 838, giving up w pop 870723.3616898305\n",
      "I am working on tract number 840 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 845 2.0 3 90.0 0.2942 114712.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 845 5.0 2 452.4 0.3495 76622.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 845 6.0 2 452.4 0.6509 76622.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 852 2.0 1 90.0 0.3215 28338.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 852 3.0 1 90.0 1.0882 28338.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 852 7.0 1 90.0 0.9583 28338.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 852 15.0 1 90.0 1.0402 28338.0\n",
      "7 yoyos for tract,wedge,wedgePop,r= 852 1 1562275.111468607 3.5209\n",
      "7 yoyos for tract,wedge,wedgePop,r= 852 1 620974.1954216365 1.7605\n",
      "8 yoyos for tract,wedge,wedgePop,r= 852 1 28338.00768332556 0.8802\n",
      "9 yoyos for tract,wedge,wedgePop,r= 852 1 496978.0956833682 1.4388\n",
      "10 yoyos for tract,wedge,wedgePop,r= 852 1 32268.888007541187 1.1595\n",
      "10 yoyos for tract,wedge,wedgePop,r= 852 1 97428.60392773221 1.2991\n",
      "11 yoyos for tract,wedge,wedgePop,r= 852 1 306118.7774086271 1.3689\n",
      "11 yoyos for tract,wedge,wedgePop,r= 852 1 200545.0161466769 1.334\n",
      "12 yoyos for tract,wedge,wedgePop,r= 852 1 130949.34062149968 1.3166\n",
      "12 yoyos for tract,wedge,wedgePop,r= 852 1 160096.19882974125 1.3253\n",
      "12 yoyos for tract,wedge,wedgePop,r= 852 1 179172.67696916428 1.3297\n",
      "I am working on tract number 860 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 869 2.0 2 90.0 0.1825 36143.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 869 3.0 2 90.0 0.5367 36143.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 879 9.0 3 90.0 0.8816 174069.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 879 10.0 3 90.0 0.9411 174069.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 879 11.0 3 90.0 1.0046 174069.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 879 16.0 3 90.0 1.0354 174069.9\n",
      "I am working on tract number 880 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 894 4.0 0 90.0 0.2997 224864.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 894 4.0 3 90.0 0.7756 120810.4\n",
      "I am working on tract number 900 of 9129 tracts\n",
      "I am working on tract number 920 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 921 2.0 0 90.0 0.2042 15866.7\n",
      "I am working on tract number 940 of 9129 tracts\n",
      "I am working on tract number 960 of 9129 tracts\n",
      "I am working on tract number 980 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 994 1 585860.5975274777 1.5461\n",
      "8 yoyos for tract,wedge,wedgePop,r= 994 1 9987.315152345342 0.7731\n",
      "9 yoyos for tract,wedge,wedgePop,r= 994 1 813762.4712897899 1.8951\n",
      "9 yoyos for tract,wedge,wedgePop,r= 994 1 536801.7118096477 1.3341\n",
      "10 yoyos for tract,wedge,wedgePop,r= 994 1 55996.413520725735 1.0536\n",
      "11 yoyos for tract,wedge,wedgePop,r= 994 1 407978.8982831617 1.1938\n",
      "11 yoyos for tract,wedge,wedgePop,r= 994 1 240440.76889287858 1.1237\n",
      "12 yoyos for tract,wedge,wedgePop,r= 994 1 125085.92141817097 1.0886\n",
      "loop31.0, tr994,wedgePops720831.63, 94177.8, 183349.2, 221742.8, 221561.8, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01222 \n",
      "   targetWP, latest drx4 are tWP,dr, 222057.5,0.9104, 222057.5,0.0175, 222057.5,0.0054, 222057.5,0.0021\n",
      "12 yoyos for tract,wedge,wedgePop,r= 994 1 183349.20037090266 1.1062\n",
      "loop32.0, tr994,wedgePops751069.01, 94177.8, 213586.6, 221742.8, 221561.8, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01222 \n",
      "   targetWP, latest drx4 are tWP,dr, 222057.5,0.9104, 222057.5,0.0088, 222057.5,0.0054, 222057.5,0.0021\n",
      "12 yoyos for tract,wedge,wedgePop,r= 994 1 213586.5758353884 1.1149\n",
      "loop33.0, tr994,wedgePops764442.16, 94177.8, 226959.7, 221742.8, 221561.8, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01222 \n",
      "   targetWP, latest drx4 are tWP,dr, 222057.5,0.9104, 222057.5,0.0044, 222057.5,0.0054, 222057.5,0.0021\n",
      "13 yoyos for tract,wedge,wedgePop,r= 994 1 226959.72382261834 1.1193\n",
      "loop34.0, tr994,wedgePops757786.93, 94177.8, 220304.5, 221742.8, 221561.8, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01322 \n",
      "   targetWP, latest drx4 are tWP,dr, 222057.5,0.9104, 222057.5,-0.0022, 222057.5,0.0054, 222057.5,0.0021\n",
      "I am working on tract number 1000 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1009 6.0 0 90.0 0.8711 226593.4\n",
      "I am working on tract number 1020 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1027 3 341296.7984545012 0.7023\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1027 3 108507.87456844904 0.3512\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1027 3 498375.1151047894 0.7886\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1027 3 130275.82504622126 0.5699\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1027 3 321181.2953530424 0.6793\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1027 3 242668.9400127228 0.6246\n",
      "12 yoyos for tract,wedge,wedgePop,r= 1027 3 165248.5617635473 0.5972\n",
      "13 yoyos for tract,wedge,wedgePop,r= 1027 3 196766.57820975108 0.6109\n",
      "14 yoyos for tract,wedge,wedgePop,r= 1027 3 179285.14026002656 0.6041\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1038 9.0 0 90.0 1.5932 167891.3\n",
      "I am working on tract number 1040 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1047 3.0 0 90.0 0.2531 74862.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1047 4.0 0 90.0 0.4784 74862.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1056 4.0 0 119.1 0.5361 15605.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1057 5.0 0 118.6 0.3599 9980.6\n",
      "I am working on tract number 1060 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1067 13.0 0 91.3 0.2368 174821.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1067 14.0 0 91.3 0.2519 174821.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1067 15.0 0 91.3 0.2681 174821.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1067 16.0 0 91.3 0.2853 174821.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1067 17.0 0 91.3 0.3036 174821.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1067 22.0 0 91.3 2.364 189151.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1067 23.0 0 91.3 2.3727 189151.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1067 24.0 0 91.3 2.3815 189151.9\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1067 1 272210.3542885268 1.0406\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1067 25.0 0 91.3 2.3903 189151.9\n",
      "loop31.0, tr1067,wedgePops837158.14, 189151.9, 267811.1, 189939.9, 190255.3, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0300 \n",
      "   targetWP, latest drx4 are tWP,dr, 190399.5,0.0089, 190399.5,0.0888, 190399.5,0.0123, 190399.5,0.0002\n",
      "loop32.0, tr1067,wedgePops771152.97, 189151.9, 201805.9, 189939.9, 190255.3, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0400 \n",
      "   targetWP, latest drx4 are tWP,dr, 190399.5,0.0089, 190399.5,-0.0458, 190399.5,0.0123, 190399.5,0.0002\n",
      "loop33.0, tr1067,wedgePops756120.77, 189151.9, 186773.7, 189939.9, 190255.3, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0400 \n",
      "   targetWP, latest drx4 are tWP,dr, 190399.5,0.0089, 190399.5,-0.0065, 190399.5,0.0123, 190399.5,0.0002\n",
      "loop34.0, tr1067,wedgePops759031.2, 189151.9, 189684.1, 189939.9, 190255.3, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0500 \n",
      "   targetWP, latest drx4 are tWP,dr, 190399.5,0.0089, 190399.5,0.0013, 190399.5,0.0123, 190399.5,0.0002\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 8.0 0 91.5 0.2243 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 9.0 0 91.5 0.2289 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 10.0 0 91.5 0.2335 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 11.0 0 91.5 0.2383 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 12.0 0 91.5 0.2432 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 13.0 0 91.5 0.2482 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 14.0 0 91.5 0.2532 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 15.0 0 91.5 0.2584 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 16.0 0 91.5 0.2637 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 17.0 0 91.5 0.2691 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 18.0 0 91.5 0.2746 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 19.0 0 91.5 0.2802 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 20.0 0 91.5 0.286 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 21.0 0 91.5 0.2918 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 22.0 0 91.5 0.2978 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 23.0 0 91.5 0.3039 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 24.0 0 91.5 0.3101 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 25.0 0 91.5 0.3164 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 26.0 0 91.5 0.3229 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 27.0 0 91.5 0.3295 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 28.0 0 91.5 0.3362 185008.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1069 29.0 0 91.5 0.3431 185008.3\n",
      "loop31.0, tr1069,wedgePops756315.33, 186385.6, 189995.5, 189986.4, 189947.9, Overedge?0, 0, 0, 0, ,Satisfied?0111,yoyo?0022 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.9104, 190087.6,0.0003, 190087.6,0.0001, 190087.6,0.0002\n",
      "loop32.0, tr1069,wedgePops756315.33, 186385.6, 189995.5, 189986.4, 189947.9, Overedge?1, 0, 0, 0, ,Satisfied?0111,yoyo?0000 \n",
      "   targetWP, latest drx4 are tWP,dr, 191321.6,0.8731, 191321.6,0.0003, 191321.6,0.0001, 191321.6,0.0002\n",
      "loop33.0, tr1069,wedgePops759551.13, 186385.6, 191067.4, 191058.1, 191040.1, Overedge?1, 0, 0, 0, ,Satisfied?0000,yoyo?0000 \n",
      "   targetWP, latest drx4 are tWP,dr, 191321.6,0.8731, 191321.6,0.0007, 191321.6,0.0003, 191321.6,0.0002\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1075 10.0 2 90.0 1.1702 186087.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1075 11.0 2 90.0 1.1889 186087.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1075 12.0 2 90.0 1.208 186087.5\n",
      "I am working on tract number 1080 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1081 10.0 0 95.9 0.3022 168424.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1081 11.0 0 95.9 0.3304 168424.0\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1083 3 270313.4839086221 3.2122\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1083 3 128027.2479214379 1.6061\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1083 3 275127.70038037095 3.6435\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1083 3 154621.79531604465 2.6248\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1083 3 269106.92643247196 3.1341\n",
      "12 yoyos for tract,wedge,wedgePop,r= 1083 3 181272.5346373937 2.8795\n",
      "13 yoyos for tract,wedge,wedgePop,r= 1083 3 250468.8885009723 3.0068\n",
      "14 yoyos for tract,wedge,wedgePop,r= 1083 3 208652.2827111629 2.9431\n",
      "need to widen edge circle beyond 0.0007571670307348528 for tract (x,y)=( -122.27833960746283 37.54993732037346\n",
      "need to widen edge circle beyond 0.0008328837338083382 for tract (x,y)=( -122.27833960746283 37.54993732037346\n",
      "need to widen edge circle beyond 0.0009161721071891721 for tract (x,y)=( -122.27833960746283 37.54993732037346\n",
      "need to widen edge circle beyond 0.0010077893179080894 for tract (x,y)=( -122.27833960746283 37.54993732037346\n",
      "need to widen edge circle beyond 0.0011085682496988984 for tract (x,y)=( -122.27833960746283 37.54993732037346\n",
      "need to widen edge circle beyond 0.0012194250746687884 for tract (x,y)=( -122.27833960746283 37.54993732037346\n",
      "need to widen edge circle beyond 0.0013413675821356674 for tract (x,y)=( -122.27833960746283 37.54993732037346\n",
      "need to widen edge circle beyond 0.0014755043403492341 for tract (x,y)=( -122.27833960746283 37.54993732037346\n",
      "need to widen edge circle beyond 0.0016230547743841578 for tract (x,y)=( -122.27833960746283 37.54993732037346\n",
      "need to widen edge circle beyond 0.0017853602518225738 for tract (x,y)=( -122.27833960746283 37.54993732037346\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "need to widen edge circle beyond 0.0006070600063778157 for tract (x,y)=( -122.31910270835424 37.57021632232603\n",
      "need to widen edge circle beyond 0.0006677660070155973 for tract (x,y)=( -122.31910270835424 37.57021632232603\n",
      "need to widen edge circle beyond 0.0007345426077171571 for tract (x,y)=( -122.31910270835424 37.57021632232603\n",
      "need to widen edge circle beyond 0.0008079968684888729 for tract (x,y)=( -122.31910270835424 37.57021632232603\n",
      "need to widen edge circle beyond 0.0008887965553377602 for tract (x,y)=( -122.31910270835424 37.57021632232603\n",
      "need to widen edge circle beyond 0.0009776762108715364 for tract (x,y)=( -122.31910270835424 37.57021632232603\n",
      "need to widen edge circle beyond 0.0010754438319586902 for tract (x,y)=( -122.31910270835424 37.57021632232603\n",
      "need to widen edge circle beyond 0.0011829882151545594 for tract (x,y)=( -122.31910270835424 37.57021632232603\n",
      "need to widen edge circle beyond 0.0013012870366700155 for tract (x,y)=( -122.31910270835424 37.57021632232603\n",
      "need to widen edge circle beyond 0.001431415740337017 for tract (x,y)=( -122.31910270835424 37.57021632232603\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1096 11.0 0 84.1 0.3055 180396.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1096 12.0 0 84.1 0.3176 180396.0\n",
      "I am working on tract number 1100 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1112 1 557513.2324588613 1.2231\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1112 1 122271.02756120206 0.6115\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1112 1 557500.6774796953 1.2227\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1112 1 521840.89885192114 0.9171\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1112 1 341451.552034156 0.7643\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1112 1 273051.8757266983 0.6879\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1112 1 184393.94272573828 0.6497\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1112 1 239514.71561174927 0.6688\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1112 1 213183.39150915394 0.6593\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1112 1 198758.13494633124 0.6545\n",
      "I am working on tract number 1120 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1127 2.0 1 90.0 0.1095 43995.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1128 2.0 2 90.0 0.1144 46199.7\n",
      "I am working on tract number 1140 of 9129 tracts\n",
      "I am working on tract number 1160 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1160 6.0 0 90.0 0.8192 183695.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1160 7.0 0 90.0 0.8404 183695.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1160 8.0 0 90.0 0.8621 183695.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1160 9.0 0 90.0 0.8844 183695.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1160 10.0 0 90.0 0.9073 183695.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1160 11.0 0 90.0 0.9308 183695.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1160 12.0 0 90.0 0.9549 183695.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1160 13.0 0 90.0 0.9796 183695.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1160 14.0 0 90.0 1.0049 183695.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1160 15.0 0 90.0 1.031 183695.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1160 16.0 0 90.0 1.0576 183695.2\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1178 2 238478.09837976622 1.0221\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1178 2 7061.174054687464 0.511\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1178 2 541294.6896794026 1.1643\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1178 2 35779.45684346027 0.8377\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1178 2 170557.6526930762 1.001\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1178 2 407957.5312889152 1.0827\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1178 2 306309.11265380506 1.0418\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1178 2 236090.69271075563 1.0214\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1178 2 201274.28246079566 1.0112\n",
      "I am working on tract number 1180 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1187 7.0 1 -272.4 0.2592 77881.2\n",
      "I am working on tract number 1200 of 9129 tracts\n",
      "I am working on tract number 1220 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1227 0 198937.6104105839 0.621\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1227 0 152942.18895816634 0.3105\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1227 0 254753.2868379383 0.6446\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1227 0 162731.67183357166 0.4776\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1227 0 170845.23375319105 0.5611\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1227 0 180114.8576565851 0.6029\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1227 0 203957.85007319658 0.6237\n",
      "I am working on tract number 1240 of 9129 tracts\n",
      "I am working on tract number 1260 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1272 0 1075650.2764928674 0.7997\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1272 0 723317.7088334311 0.3998\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1272 0 107923.1620255775 0.1999\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1272 0 459076.87770766165 0.3626\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1272 0 115202.94732057594 0.2812\n",
      "we have 2 non-opposing shorted wedges for tract no 1278\n",
      "I am working on tract number 1280 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1283 4.0 0 140.5 0.2303 18110.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1283 7.0 0 140.5 1.8606 206457.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1283 8.0 0 140.5 1.7477 206457.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1283 9.0 0 140.5 1.6416 206457.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1284 4.0 3 90.0 0.2099 142051.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1284 10.0 0 97.7 0.2325 164134.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1285 2.0 2 90.0 1.0473 1384.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1285 6.0 2 90.0 0.9123 1384.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1287 10.0 0 83.7 0.4347 209465.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1288 9.0 0 85.0 0.4148 183745.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1288 10.0 0 85.0 0.4254 183745.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1288 11.0 0 85.0 0.4363 183745.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1288 12.0 0 85.0 0.4475 183745.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1288 13.0 0 85.0 0.459 183745.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1288 14.0 0 85.0 0.4708 183745.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1288 15.0 0 85.0 0.4829 183745.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1294 9.0 0 116.3 0.3978 251384.8\n",
      "I am working on tract number 1300 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1308 2 196730.10034617328 0.58\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1308 2 57710.513462122035 0.29\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1308 2 1244950.4357641363 0.8286\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1308 2 127854.31516239326 0.5593\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1308 2 835944.4179019686 0.6939\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1308 2 455222.8237057825 0.6266\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1308 2 262220.51031115034 0.5929\n",
      "12 yoyos for tract,wedge,wedgePop,r= 1308 2 178932.12821595347 0.5761\n",
      "13 yoyos for tract,wedge,wedgePop,r= 1308 2 217857.47192112246 0.5845\n",
      "13 yoyos for tract,wedge,wedgePop,r= 1308 2 198051.03286189318 0.5803\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1311 2 842489.355349355 1.0801\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1311 2 48109.038922558306 0.54\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1311 2 841819.7303320392 1.0791\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1311 2 646022.6847390286 0.8096\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1311 2 423495.99975145154 0.6748\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1311 2 159570.79518256336 0.6074\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1311 2 297180.2459248558 0.6411\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1311 2 223243.76256442448 0.6243\n",
      "I am working on tract number 1320 of 9129 tracts\n",
      "I am working on tract number 1340 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1347 2 1309653.7808792612 0.9077\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1347 2 908832.9256582237 0.4538\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1347 2 82058.07158104517 0.2269\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1347 2 675959.4789287178 0.4099\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1347 2 247037.86870627198 0.3184\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1347 2 85968.01527641292 0.2726\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1347 2 136603.51050095868 0.2955\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1352 3 331546.41785809415 1.1246\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1352 3 90021.25277285057 0.5623\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1352 3 317551.356345042 1.0314\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1352 3 283257.440593835 0.7969\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1352 3 147492.92619844706 0.6796\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1352 3 227288.59592134436 0.7382\n",
      "12 yoyos for tract,wedge,wedgePop,r= 1352 3 179161.44409697718 0.7089\n",
      "13 yoyos for tract,wedge,wedgePop,r= 1352 3 201215.3830732057 0.7236\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1353 5.0 0 90.0 0.3458 168599.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1353 6.0 0 90.0 0.3779 168599.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1353 7.0 0 90.0 0.413 168599.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1353 8.0 0 90.0 0.4512 168599.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1353 9.0 0 90.0 0.4931 168599.6\n",
      "I am working on tract number 1360 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1373 0 194313.83834068972 1.1245\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1373 0 72270.95165648105 0.5622\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1373 0 494815.91834394645 1.4059\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1373 0 101161.19054032658 0.9841\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1373 0 380798.2976842743 1.195\n",
      "12 yoyos for tract,wedge,wedgePop,r= 1373 0 144930.28837624774 1.0895\n",
      "13 yoyos for tract,wedge,wedgePop,r= 1373 0 234217.78846073564 1.1422\n",
      "14 yoyos for tract,wedge,wedgePop,r= 1373 0 178867.46518008926 1.1159\n",
      "15 yoyos for tract,wedge,wedgePop,r= 1373 0 203382.70473020032 1.1291\n",
      "I am working on tract number 1380 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1395 3 198312.59398251004 1.6478\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1395 3 109897.03440616293 0.8239\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1395 3 197620.78541871015 1.6038\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1395 3 158943.85182001186 1.2139\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1395 3 165037.85832975883 1.4088\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1398 4.0 2 90.0 0.4132 138158.9\n",
      "I am working on tract number 1400 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1402 7.0 0 142.1 1.6407 203944.1\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1402 0 203944.05408180985 1.6124\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1402 0 24461.37104076217 0.8062\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1402 0 203944.05408180578 1.6113\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1402 0 57393.140043347026 1.2088\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1402 0 135311.8310922315 1.41\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1402 0 200449.65416106116 1.5107\n",
      "12 yoyos for tract,wedge,wedgePop,r= 1402 0 181099.29686380122 1.4604\n",
      "13 yoyos for tract,wedge,wedgePop,r= 1402 0 197574.62109601367 1.4855\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1403 5.0 0 143.2 0.7707 170232.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1403 6.0 0 143.2 0.8363 170232.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1403 7.0 0 143.2 0.9074 170232.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1403 8.0 0 143.2 0.9846 170232.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1403 9.0 0 143.2 1.0684 170232.8\n",
      "I am working on tract number 1420 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1424 2.0 3 90.0 0.2783 49275.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1424 6.0 0 136.8 0.3033 62328.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1424 7.0 0 136.8 0.6428 62328.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1424 13.0 0 136.8 1.2883 399542.9\n",
      "I am working on tract number 1440 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1440 10.0 0 99.7 0.7555 144969.5\n",
      "we have 2 non-opposing shorted wedges for tract no 1456\n",
      "I am working on tract number 1460 of 9129 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 1463\n",
      "we have 2 non-opposing shorted wedges for tract no 1464\n",
      "I am working on tract number 1480 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1485 5.0 2 90.0 0.346 152609.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1485 6.0 2 90.0 0.4062 152609.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1485 7.0 2 90.0 0.477 152609.6\n",
      "I am working on tract number 1500 of 9129 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 1501\n",
      "I am working on tract number 1520 of 9129 tracts\n",
      "I am working on tract number 1540 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1542 2.0 1 90.0 1.0319 648.0\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1552 2 203661.38641056753 0.9076\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1552 2 161222.67386491844 0.4538\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1552 2 204108.25089891133 0.9277\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1552 2 170936.65127281373 0.6907\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1552 2 183371.48154761398 0.8092\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1552 2 200103.2135861187 0.8684\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1556 3 14024.21522600518 0.8413\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1556 3 430667.9084589094 2.6536\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1556 3 316417.62254026806 1.7475\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1556 3 84769.2874699118 1.2944\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1556 3 263447.4600630187 1.5209\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1556 3 138471.34581300235 1.4076\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1556 3 207091.54345834284 1.4643\n",
      "12 yoyos for tract,wedge,wedgePop,r= 1556 3 242827.81602256 1.4926\n",
      "13 yoyos for tract,wedge,wedgePop,r= 1556 3 227811.8826547437 1.4784\n",
      "I am working on tract number 1560 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1572 6.0 0 83.7 0.4404 165787.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1572 7.0 0 83.7 0.4871 165787.0\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1572 0 282966.86191529955 1.5821\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1572 0 269554.64646881114 0.791\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1572 0 165786.98522369197 0.3955\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1572 0 255869.52917947358 0.7491\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1572 0 166981.24327380193 0.5723\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1572 0 183831.9204517753 0.6607\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1572 0 209683.91402518423 0.7049\n",
      "I am working on tract number 1580 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1596 5.0 3 90.0 0.6927 201192.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1596 6.0 3 90.0 0.6636 201192.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1596 7.0 3 90.0 0.6358 201192.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1596 8.0 3 90.0 0.6091 201192.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1596 9.0 3 90.0 0.5835 201192.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1596 10.0 3 90.0 0.559 201192.2\n",
      "I am working on tract number 1600 of 9129 tracts\n",
      "I am working on tract number 1620 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1628 4.0 3 90.0 0.2406 141870.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1630 5.0 0 126.3 0.662 83425.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1633 5.0 0 143.9 1.1651 183392.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1633 6.0 0 143.9 1.1967 183392.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1633 7.0 0 143.9 1.2292 183392.1\n",
      "I am working on tract number 1640 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1654 5.0 0 92.3 0.1542 181452.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1657 2.0 3 90.0 0.2338 25866.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1658 5.0 0 121.6 0.5695 96491.4\n",
      "I am working on tract number 1660 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1664 5.0 0 90.0 0.751 93683.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1668 2.0 0 90.0 0.1356 38081.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1668 7.0 0 131.2 0.6028 134398.5\n",
      "I am working on tract number 1680 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 8.0 0 135.5 0.889 196079.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 9.0 0 135.5 0.8685 196079.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 10.0 0 135.5 0.8484 196079.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 11.0 0 135.5 0.8288 196079.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 12.0 0 135.5 0.8097 196079.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 13.0 0 135.5 0.791 196079.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 14.0 0 135.5 0.7727 196079.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 15.0 0 135.5 0.7549 196079.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 16.0 0 135.5 0.7375 196079.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 17.0 0 135.5 0.7204 196079.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 18.0 0 135.5 0.7038 196079.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 19.0 0 135.5 0.6875 196079.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 20.0 0 135.5 0.6716 196079.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 21.0 0 135.5 0.6561 196079.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 22.0 0 135.5 0.641 196079.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 23.0 0 135.5 0.6262 196079.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 24.0 0 135.5 0.6117 196079.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 25.0 0 135.5 0.5976 196079.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 26.0 0 135.5 0.5838 196079.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 27.0 0 135.5 0.5703 196079.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1680 28.0 0 135.5 0.5571 196079.0\n",
      "loop31.0, tr1680,wedgePops754985.27, 184750.8, 189784.8, 190242.0, 190207.6, Overedge?0, 0, 0, 0, ,Satisfied?0111,yoyo?2011 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.2111, 190087.6,0.0086, 190087.6,-0.0002, 190087.6,-0.0001\n",
      "loop32.0, tr1680,wedgePops756553.34, 186318.9, 189784.8, 190242.0, 190207.6, Overedge?0, 0, 0, 0, ,Satisfied?0111,yoyo?2011 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0053, 190087.6,0.0086, 190087.6,-0.0002, 190087.6,-0.0001\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1692 3 195605.11079689924 1.2329\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1692 3 10834.114010365214 0.6164\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1692 3 220388.3930711605 1.2418\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1692 3 19171.309353463468 0.9291\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1692 3 73406.86809347472 1.0855\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1692 3 130651.90263985633 1.1637\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1692 3 151823.24689244688 1.2027\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1692 3 173656.21386364073 1.2223\n",
      "I am working on tract number 1700 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1705 3 877071.774660518 2.4962\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1705 3 247784.98526931566 1.2481\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1705 3 135495.95220424823 0.624\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1705 3 148883.22784477996 1.052\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1705 3 255306.66922272695 1.2659\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1705 3 172433.72500205925 1.1589\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1705 3 224031.86767086893 1.2124\n",
      "I am working on tract number 1720 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1731 11.0 0 103.9 0.2777 180173.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1731 12.0 0 103.9 0.289 180173.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1731 13.0 0 103.9 0.3007 180173.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1731 14.0 0 103.9 0.313 180173.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1731 15.0 0 103.9 0.3257 180173.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1731 16.0 0 103.9 0.339 180173.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1731 17.0 0 103.9 0.3528 180173.1\n",
      "I am working on tract number 1740 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1750 2.0 3 90.0 0.8067 261254.2\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1758 3 1339770.880303296 0.4857\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1758 3 418892.0973646466 0.2429\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1758 3 37118.91757444205 0.1214\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1758 3 335255.58316613117 0.2341\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1758 3 46227.7712673198 0.1778\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1758 3 115293.84313813839 0.2059\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1758 3 200382.47387208263 0.22\n",
      "12 yoyos for tract,wedge,wedgePop,r= 1758 3 150582.27080526986 0.213\n",
      "12 yoyos for tract,wedge,wedgePop,r= 1758 3 173319.17756613196 0.2165\n",
      "12 yoyos for tract,wedge,wedgePop,r= 1758 3 186728.0188793007 0.2183\n",
      "I am working on tract number 1760 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1774 4.0 2 90.0 0.2368 136622.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1774 11.0 0 107.1 0.4 168387.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1776 8.0 0 128.0 0.8585 142328.9\n",
      "I am working on tract number 1780 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1783 3 457865.7399825121 0.8726\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1783 3 45633.46883478045 0.4363\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1783 3 465562.00675418106 0.9177\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1783 3 335243.2018855141 0.677\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1783 3 118946.16112775388 0.5567\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1783 3 222036.3127069351 0.6168\n",
      "12 yoyos for tract,wedge,wedgePop,r= 1783 3 164461.72959166215 0.5867\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1799 0 216816.93822093785 0.944\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1799 0 140205.2328292732 0.472\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1799 0 217772.75485369161 0.9533\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1799 0 151135.91769006004 0.7126\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1799 0 200982.98784068698 0.833\n",
      "12 yoyos for tract,wedge,wedgePop,r= 1799 0 169409.95555474507 0.7728\n",
      "I am working on tract number 1800 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1808 2.0 0 90.0 0.3008 20470.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1810 6.0 3 90.0 0.3138 168701.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1810 7.0 3 90.0 0.3428 168701.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1810 8.0 3 90.0 0.3744 168701.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1810 9.0 3 90.0 0.4089 168701.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1810 10.0 3 90.0 0.4467 168701.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1812 2.0 1 90.0 0.2436 19942.3\n",
      "I am working on tract number 1820 of 9129 tracts\n",
      "I am working on tract number 1840 of 9129 tracts\n",
      "I am working on tract number 1860 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1866 3.0 0 90.0 1.7964 197143.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1878 10.0 0 130.9 0.7638 188573.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1879 2.0 0 90.0 0.3642 11113.4\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1879 2 1163078.372436527 2.6713\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1879 2 196835.57482783461 1.3356\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1879 2 62443.2243079755 0.6678\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1879 2 77669.81086392996 1.1311\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1879 2 235611.49872072233 1.3627\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1879 2 125438.5614394861 1.2469\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1879 2 167493.18123601252 1.3048\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1879 2 194597.4772245578 1.3338\n",
      "12 yoyos for tract,wedge,wedgePop,r= 1879 2 180031.79695015796 1.3193\n",
      "I am working on tract number 1880 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1880 6.0 2 90.0 0.9684 179392.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1880 9.0 2 90.0 1.2064 235075.6\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1891 0 308692.67047194974 0.6405\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1891 0 143413.79355666754 0.3202\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1891 0 304822.80820408254 0.609\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1891 0 271377.9394901461 0.4646\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1891 0 204198.5734452883 0.3924\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1891 0 165595.42167945637 0.3563\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1891 0 183637.88387632355 0.3744\n",
      "I am working on tract number 1900 of 9129 tracts\n",
      "I am working on tract number 1920 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1924 0 310448.93541520217 1.4689\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1924 0 154551.26384049546 0.7344\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1924 0 310672.07638838876 1.4708\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1924 0 164450.0316156912 1.1026\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1924 0 261163.63068825772 1.2867\n",
      "loop31.0, tr1924,wedgePops742056.36, 171810.3, 190287.3, 190026.5, 189932.2, Overedge?0, 0, 0, 0, ,Satisfied?0111,yoyo?11302 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,-0.092, 190087.6,-0.012, 190087.6,0.0195, 190087.6,0.0001\n",
      "12 yoyos for tract,wedge,wedgePop,r= 1924 0 171810.2759333301 1.1947\n",
      "loop32.0, tr1924,wedgePops791426.64, 221180.6, 190287.3, 190026.5, 189932.2, Overedge?0, 0, 0, 0, ,Satisfied?0111,yoyo?12302 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.046, 190087.6,-0.012, 190087.6,0.0195, 190087.6,0.0001\n",
      "13 yoyos for tract,wedge,wedgePop,r= 1924 0 221180.55659859237 1.2407\n",
      "loop33.0, tr1924,wedgePops760352.4, 190106.3, 190287.3, 190026.5, 189932.2, Overedge?0, 0, 0, 0, ,Satisfied?0111,yoyo?13302 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,-0.023, 190087.6,-0.012, 190087.6,0.0195, 190087.6,0.0001\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1925 0 289723.9829018359 1.9657\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1925 0 133561.38218883888 0.9828\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1925 0 289744.20326690085 1.9724\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1925 0 280005.03734010056 1.4776\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1925 0 228666.22015395458 1.2302\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1925 0 138419.7361756462 1.1065\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1925 0 178434.07162644825 1.1684\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1925 0 216609.83063607966 1.1993\n",
      "loop31.0, tr1925,wedgePops768978.09, 198657.8, 189926.7, 190252.7, 190140.8, Overedge?0, 0, 0, 0, ,Satisfied?0111,yoyo?11113 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,-0.0155, 190087.6,-0.0316, 190087.6,-0.0025, 190087.6,-0.041\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1925 0 198657.83983753432 1.1839\n",
      "loop32.0, tr1925,wedgePops759105.25, 188785.0, 189926.7, 190252.7, 190140.8, Overedge?0, 0, 0, 0, ,Satisfied?0111,yoyo?11113 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,-0.0077, 190087.6,-0.0316, 190087.6,-0.0025, 190087.6,-0.041\n",
      "I am working on tract number 1940 of 9129 tracts\n",
      "I am working on tract number 1960 of 9129 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 1969\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1970 3.0 1 90.0 1.6067 217916.9\n",
      "we have 2 non-opposing shorted wedges for tract no 1971\n",
      "I am working on tract number 1980 of 9129 tracts\n",
      "I am working on tract number 2000 of 9129 tracts\n",
      "I am working on tract number 2020 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2038 2.0 0 90.0 0.8251 245992.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2038 3.0 0 90.0 0.6754 245992.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2038 4.0 0 90.0 0.5529 245992.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2038 5.0 0 90.0 0.4526 245992.5\n",
      "I am working on tract number 2040 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2052 4.0 2 90.0 0.4117 141432.9\n",
      "I am working on tract number 2060 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2070 6.0 2 452.4 0.3992 27337.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2076 4.0 2 452.4 0.2582 39092.6\n",
      "I am working on tract number 2080 of 9129 tracts\n",
      "I am working on tract number 2100 of 9129 tracts\n",
      "I am working on tract number 2120 of 9129 tracts\n",
      "I am working on tract number 2140 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2147 6.0 1 90.0 1.0793 272715.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2147 7.0 1 90.0 0.812 272715.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2149 4.0 0 141.2 0.4643 17717.3\n",
      "I am working on tract number 2160 of 9129 tracts\n",
      "I am working on tract number 2180 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2186 2.0 2 90.0 0.8089 1558.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2186 5.0 0 143.5 0.657 4049.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2187 4.0 0 133.3 0.351 46662.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2192 5.0 0 143.0 0.5342 9691.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2193 2.0 3 90.0 0.6348 3658.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2195 4.0 0 142.6 0.567 10439.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2196 2.0 1 90.0 0.8984 1571.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2196 6.0 1 90.0 0.8939 1571.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2196 10.0 1 90.0 0.8942 1571.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2196 12.0 1 90.0 1.5368 724921.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2196 15.0 0 143.4 0.6293 5538.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2197 2.0 1 90.0 0.3058 40005.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2197 5.0 0 139.8 0.4658 25596.4\n",
      "I am working on tract number 2200 of 9129 tracts\n",
      "I am working on tract number 2220 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2230 4.0 0 140.7 0.501 21734.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2232 2.0 2 90.0 1.0922 641.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2234 4.0 0 137.4 0.2335 44907.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2235 2.0 1 90.0 0.1705 91272.7\n",
      "I am working on tract number 2240 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2243 5.0 2 90.0 1.0234 217712.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2243 6.0 2 90.0 0.9227 217712.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2243 7.0 2 90.0 0.8319 217712.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2243 8.0 2 90.0 0.7501 217712.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2243 9.0 2 90.0 0.6763 217712.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2243 10.0 2 90.0 0.6097 217712.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2244 6.0 0 122.2 0.2085 95436.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2244 7.0 0 122.2 0.3372 95436.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2244 8.0 0 122.2 0.5452 95436.3\n",
      "7 yoyos for tract,wedge,wedgePop,r= 2257 1 1158230.3924248174 2.1682\n",
      "8 yoyos for tract,wedge,wedgePop,r= 2257 1 185607.08206219308 1.0841\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2257 1 1156585.009745554 2.1644\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2257 1 748972.9160512825 1.6242\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2257 1 587655.8029413123 1.3542\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2257 1 506107.1031562109 1.2191\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2257 1 389498.74556218955 1.1516\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2257 1 303681.8852155455 1.1178\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2257 1 249881.22987473602 1.101\n",
      "loop31.0, tr2257,wedgePops757118.59, 97794.7, 218023.0, 220699.5, 220601.4, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0922 \n",
      "   targetWP, latest drx4 are tWP,dr, 220851.9,0.9104, 220851.9,-0.0084, 220851.9,0.0006, 220851.9,0.0039\n",
      "I am working on tract number 2260 of 9129 tracts\n",
      "need to widen edge circle beyond 0.0008182041950547977 for tract (x,y)=( -122.15531716618847 37.68450573332334\n",
      "need to widen edge circle beyond 0.0009000246145602776 for tract (x,y)=( -122.15531716618847 37.68450573332334\n",
      "need to widen edge circle beyond 0.0009900270760163053 for tract (x,y)=( -122.15531716618847 37.68450573332334\n",
      "need to widen edge circle beyond 0.001089029783617936 for tract (x,y)=( -122.15531716618847 37.68450573332334\n",
      "need to widen edge circle beyond 0.0011979327619797296 for tract (x,y)=( -122.15531716618847 37.68450573332334\n",
      "need to widen edge circle beyond 0.0013177260381777027 for tract (x,y)=( -122.15531716618847 37.68450573332334\n",
      "need to widen edge circle beyond 0.001449498641995473 for tract (x,y)=( -122.15531716618847 37.68450573332334\n",
      "need to widen edge circle beyond 0.0015944485061950204 for tract (x,y)=( -122.15531716618847 37.68450573332334\n",
      "need to widen edge circle beyond 0.0017538933568145227 for tract (x,y)=( -122.15531716618847 37.68450573332334\n",
      "need to widen edge circle beyond 0.001929282692495975 for tract (x,y)=( -122.15531716618847 37.68450573332334\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "I am working on tract number 2280 of 9129 tracts\n",
      "need to widen edge circle beyond 0.0005435943135311112 for tract (x,y)=( -122.11353930454756 37.69926552310377\n",
      "need to widen edge circle beyond 0.0005979537448842224 for tract (x,y)=( -122.11353930454756 37.69926552310377\n",
      "need to widen edge circle beyond 0.0006577491193726447 for tract (x,y)=( -122.11353930454756 37.69926552310377\n",
      "need to widen edge circle beyond 0.0007235240313099092 for tract (x,y)=( -122.11353930454756 37.69926552310377\n",
      "need to widen edge circle beyond 0.0007958764344409002 for tract (x,y)=( -122.11353930454756 37.69926552310377\n",
      "need to widen edge circle beyond 0.0008754640778849903 for tract (x,y)=( -122.11353930454756 37.69926552310377\n",
      "need to widen edge circle beyond 0.0009630104856734894 for tract (x,y)=( -122.11353930454756 37.69926552310377\n",
      "need to widen edge circle beyond 0.0010593115342408385 for tract (x,y)=( -122.11353930454756 37.69926552310377\n",
      "need to widen edge circle beyond 0.0011652426876649223 for tract (x,y)=( -122.11353930454756 37.69926552310377\n",
      "need to widen edge circle beyond 0.0012817669564314147 for tract (x,y)=( -122.11353930454756 37.69926552310377\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "7 yoyos for tract,wedge,wedgePop,r= 2291 2 216890.815463813 5.2456\n",
      "8 yoyos for tract,wedge,wedgePop,r= 2291 2 115271.46537029494 2.6228\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2291 2 218321.47260179085 5.2764\n",
      "10 yoyos for tract,wedge,wedgePop,r= 2291 2 164262.6386431614 3.9496\n",
      "10 yoyos for tract,wedge,wedgePop,r= 2291 2 172619.36796238556 4.613\n",
      "7 yoyos for tract,wedge,wedgePop,r= 2293 0 202714.7766490717 1.1425\n",
      "8 yoyos for tract,wedge,wedgePop,r= 2293 0 26989.264139002393 0.5712\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2293 0 280810.2020074924 1.2925\n",
      "10 yoyos for tract,wedge,wedgePop,r= 2293 0 34067.82156953507 0.9319\n",
      "10 yoyos for tract,wedge,wedgePop,r= 2293 0 145884.59491966837 1.1122\n",
      "11 yoyos for tract,wedge,wedgePop,r= 2293 0 263338.73541306646 1.2023\n",
      "11 yoyos for tract,wedge,wedgePop,r= 2293 0 235447.60435408194 1.1573\n",
      "12 yoyos for tract,wedge,wedgePop,r= 2293 0 183857.51444505487 1.1347\n",
      "13 yoyos for tract,wedge,wedgePop,r= 2293 0 211446.72782218287 1.146\n",
      "13 yoyos for tract,wedge,wedgePop,r= 2293 0 197388.34100244188 1.1404\n",
      "I am working on tract number 2300 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2314 5.0 2 452.4 0.1622 47756.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2315 5.0 2 452.4 0.1766 64565.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2319 12.0 1 39.4 2.399 196075.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2319 18.0 1 39.4 2.3951 196075.0\n",
      "7 yoyos for tract,wedge,wedgePop,r= 2319 1 196075.01477868098 2.5162\n",
      "I am working on tract number 2320 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2325 3.0 1 90.0 0.1911 96825.1\n",
      "we have 2 non-opposing shorted wedges for tract no 2332\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2333 3.0 3 90.0 0.5688 118050.9\n",
      "I am working on tract number 2340 of 9129 tracts\n",
      "I am working on tract number 2360 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2361 5.0 1 -272.4 0.3963 71623.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2365 2.0 0 90.0 0.3601 4177.9\n",
      "7 yoyos for tract,wedge,wedgePop,r= 2372 3 430288.87059972004 1.0483\n",
      "8 yoyos for tract,wedge,wedgePop,r= 2372 3 208071.684571929 0.5241\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2372 3 532427.4314031433 1.0852\n",
      "10 yoyos for tract,wedge,wedgePop,r= 2372 3 255097.61725882714 0.8047\n",
      "11 yoyos for tract,wedge,wedgePop,r= 2372 3 299633.68494194694 0.9449\n",
      "12 yoyos for tract,wedge,wedgePop,r= 2372 3 261322.72742566548 0.8748\n",
      "12 yoyos for tract,wedge,wedgePop,r= 2372 3 268640.23250176373 0.9099\n",
      "12 yoyos for tract,wedge,wedgePop,r= 2372 3 280077.10344234784 0.9274\n",
      "we have 2 non-opposing shorted wedges for tract no 2373\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2378 4.0 2 247.7 0.3728 13611.7\n",
      "I am working on tract number 2380 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2388 8.0 0 133.9 0.3524 69677.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2388 9.0 0 133.9 0.6969 69677.4\n",
      "I am working on tract number 2400 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2418 3.0 1 90.0 0.3182 42737.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2418 4.0 1 90.0 0.8476 42737.9\n",
      "I am working on tract number 2420 of 9129 tracts\n",
      "I am working on tract number 2440 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 2453 3 314158.0601224714 2.5782\n",
      "8 yoyos for tract,wedge,wedgePop,r= 2453 3 136289.89188150474 1.2891\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2453 3 314164.6018928062 2.5827\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2453 3 249569.1880893231 1.9359\n",
      "10 yoyos for tract,wedge,wedgePop,r= 2453 3 144656.71237962524 1.6125\n",
      "10 yoyos for tract,wedge,wedgePop,r= 2453 3 152772.20111580123 1.7742\n",
      "we have 2 non-opposing shorted wedges for tract no 2459\n",
      "I am working on tract number 2460 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2470 6.0 3 90.0 0.8758 176720.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2470 7.0 3 90.0 0.9246 176720.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2470 8.0 3 90.0 0.9761 176720.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2470 9.0 3 90.0 1.0305 176720.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2470 10.0 3 90.0 1.0879 176720.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2470 11.0 3 90.0 1.1484 176720.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2472 12.0 1 72.3 2.6602 232394.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2472 17.0 1 72.3 2.9604 232394.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2472 18.0 1 72.3 2.7657 232394.9\n",
      "I am working on tract number 2480 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2480 7.0 1 39.6 0.2349 166365.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2480 8.0 1 39.6 0.2592 166365.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2486 6.0 2 90.0 0.2832 179129.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2495 7.0 3 75.1 0.2353 144992.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2495 8.0 3 75.1 0.2865 144992.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2495 9.0 3 75.1 0.3488 144992.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2495 10.0 3 75.1 0.4247 144992.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2495 11.0 3 75.1 0.5171 144992.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2495 12.0 3 75.1 0.6296 144992.4\n",
      "I am working on tract number 2500 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2508 5.0 2 452.4 0.2357 23652.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2511 12.0 1 70.9 2.8268 225481.2\n",
      "we have 2 non-opposing shorted wedges for tract no 2512\n",
      "I am working on tract number 2520 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 2522 1 530656.9856383961 0.9497\n",
      "8 yoyos for tract,wedge,wedgePop,r= 2522 1 95972.3724159961 0.4748\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2522 1 530966.4842529665 0.9511\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2522 1 446622.918305383 0.713\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2522 1 256520.14587462856 0.5939\n",
      "10 yoyos for tract,wedge,wedgePop,r= 2522 1 116962.88784243402 0.5344\n",
      "7 yoyos for tract,wedge,wedgePop,r= 2526 2 228257.70867523394 0.5505\n",
      "8 yoyos for tract,wedge,wedgePop,r= 2526 2 136867.38655388178 0.2752\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2526 2 228205.3824503686 0.5501\n",
      "10 yoyos for tract,wedge,wedgePop,r= 2526 2 163459.36979461415 0.4127\n",
      "11 yoyos for tract,wedge,wedgePop,r= 2526 2 216532.85682147523 0.4814\n",
      "11 yoyos for tract,wedge,wedgePop,r= 2526 2 195073.31242259959 0.447\n",
      "12 yoyos for tract,wedge,wedgePop,r= 2526 2 177927.9750456632 0.4299\n",
      "12 yoyos for tract,wedge,wedgePop,r= 2526 2 186444.7270321541 0.4385\n",
      "I am working on tract number 2540 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2544 16.0 1 85.5 2.9147 234572.3\n",
      "7 yoyos for tract,wedge,wedgePop,r= 2549 3 568738.5441662516 1.0132\n",
      "8 yoyos for tract,wedge,wedgePop,r= 2549 3 66643.96462758165 0.5066\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2549 3 568970.1846801017 1.0138\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2549 3 440870.3046070716 0.7602\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2549 3 236194.33790322507 0.6334\n",
      "10 yoyos for tract,wedge,wedgePop,r= 2549 3 85556.23374814022 0.57\n",
      "10 yoyos for tract,wedge,wedgePop,r= 2549 3 136796.04853081942 0.6017\n",
      "I am working on tract number 2560 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 2569 0 2526933.671303933 2.0967\n",
      "8 yoyos for tract,wedge,wedgePop,r= 2569 0 96313.4751299643 1.0484\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2569 0 2562769.652921372 2.2218\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2569 0 2060992.080308363 1.6351\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2569 0 1203400.910440749 1.3417\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2569 0 333932.6942333323 1.195\n",
      "10 yoyos for tract,wedge,wedgePop,r= 2569 0 106180.55275502263 1.1217\n",
      "10 yoyos for tract,wedge,wedgePop,r= 2569 0 171055.94989771795 1.1584\n",
      "11 yoyos for tract,wedge,wedgePop,r= 2569 0 248149.45983097615 1.1767\n",
      "11 yoyos for tract,wedge,wedgePop,r= 2569 0 208590.43045563003 1.1675\n",
      "I am working on tract number 2580 of 9129 tracts\n",
      "I am working on tract number 2600 of 9129 tracts\n",
      "I am working on tract number 2620 of 9129 tracts\n",
      "I am working on tract number 2640 of 9129 tracts\n",
      "I am working on tract number 2660 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2673 8.0 3 90.0 2.6564 215569.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2673 14.0 3 90.0 2.7938 215569.5\n",
      "7 yoyos for tract,wedge,wedgePop,r= 2673 3 215569.45472333807 3.4928\n",
      "loop31.0, tr2673,wedgePops738678.16, 133726.5, 197642.0, 204778.4, 202531.2, Overedge?1, 0, 0, 0, ,Satisfied?0000,yoyo?0100 \n",
      "   targetWP, latest drx4 are tWP,dr, 208874.6,0.9104, 208874.6,0.0108, 208874.6,0.0046, 208874.6,0.021\n",
      "loop32.0, tr2673,wedgePops756398.64, 133726.5, 208552.6, 208080.0, 206039.5, Overedge?1, 0, 0, 0, ,Satisfied?0000,yoyo?0100 \n",
      "   targetWP, latest drx4 are tWP,dr, 208874.6,0.9104, 208874.6,0.0031, 208874.6,0.001, 208874.6,0.0059\n",
      "loop33.0, tr2673,wedgePops758633.68, 133726.5, 208552.6, 208714.3, 207640.3, Overedge?1, 0, 0, 0, ,Satisfied?0100,yoyo?0100 \n",
      "   targetWP, latest drx4 are tWP,dr, 208874.6,0.9104, 208874.6,0.0031, 208874.6,0.0002, 208874.6,0.0037\n",
      "I am working on tract number 2680 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2687 4.0 3 90.0 0.4255 83722.9\n",
      "I am working on tract number 2700 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 2703 0 249740.46892053477 1.0391\n",
      "8 yoyos for tract,wedge,wedgePop,r= 2703 0 102602.86907345799 0.5196\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2703 0 244048.99397501707 1.0024\n",
      "10 yoyos for tract,wedge,wedgePop,r= 2703 0 150049.00733470934 0.761\n",
      "11 yoyos for tract,wedge,wedgePop,r= 2703 0 235770.85949875368 0.8817\n",
      "11 yoyos for tract,wedge,wedgePop,r= 2703 0 208238.83891223063 0.8213\n",
      "12 yoyos for tract,wedge,wedgePop,r= 2703 0 176663.615969373 0.7911\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2713 4.0 3 90.0 0.2518 153356.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2713 9.0 2 452.4 0.2117 162414.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2713 10.0 2 452.4 0.2377 162414.2\n",
      "I am working on tract number 2720 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2734 2.0 3 90.0 0.796 269030.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2734 3.0 3 90.0 0.6057 269030.6\n",
      "I am working on tract number 2740 of 9129 tracts\n",
      "I am working on tract number 2760 of 9129 tracts\n",
      "I am working on tract number 2780 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2792 4.0 3 90.0 0.2467 153485.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2792 5.0 3 90.0 0.2885 153485.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2792 11.0 2 452.4 1.1329 160868.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2798 4.0 0 131.1 0.2813 73561.3\n",
      "I am working on tract number 2800 of 9129 tracts\n",
      "I am working on tract number 2820 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2820 2.0 1 90.0 0.666 431724.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2820 3.0 1 90.0 0.333 431724.8\n",
      "we have 2 non-opposing shorted wedges for tract no 2828\n",
      "I am working on tract number 2840 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 2841 0 194691.40163663088 1.0103\n",
      "8 yoyos for tract,wedge,wedgePop,r= 2841 0 59198.78146359316 0.5052\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2841 0 219947.8642558455 1.0843\n",
      "10 yoyos for tract,wedge,wedgePop,r= 2841 0 126281.40968100782 0.7947\n",
      "10 yoyos for tract,wedge,wedgePop,r= 2841 0 138951.6417410164 0.9395\n",
      "11 yoyos for tract,wedge,wedgePop,r= 2841 0 196137.8505919405 1.0119\n",
      "12 yoyos for tract,wedge,wedgePop,r= 2841 0 158374.26400515903 0.9757\n",
      "12 yoyos for tract,wedge,wedgePop,r= 2841 0 177167.9056300971 0.9938\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2842 6.0 1 45.3 0.2701 108538.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2842 7.0 1 45.3 0.4011 108538.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2842 8.0 1 45.3 0.5956 108538.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2842 9.0 1 45.3 0.8845 108538.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2846 3.0 0 143.3 1.1028 3088.6\n",
      "we have 2 non-opposing shorted wedges for tract no 2858\n",
      "I am working on tract number 2860 of 9129 tracts\n",
      "I am working on tract number 2880 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2882 4.0 0 90.0 0.3424 237093.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2882 5.0 0 90.0 0.2887 237093.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2885 6.0 0 129.8 0.4075 55063.5\n",
      "7 yoyos for tract,wedge,wedgePop,r= 2885 0 372274.12931732315 1.281\n",
      "8 yoyos for tract,wedge,wedgePop,r= 2885 0 61518.174622501596 0.6405\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2885 0 396801.4898443956 1.5597\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2885 0 355634.8546904964 1.1001\n",
      "10 yoyos for tract,wedge,wedgePop,r= 2885 0 70061.27929707064 0.8703\n",
      "10 yoyos for tract,wedge,wedgePop,r= 2885 0 176360.85413208354 0.9852\n",
      "11 yoyos for tract,wedge,wedgePop,r= 2885 0 271349.71676960133 1.0427\n",
      "11 yoyos for tract,wedge,wedgePop,r= 2885 0 221852.20997975382 1.0139\n",
      "11 yoyos for tract,wedge,wedgePop,r= 2885 0 198483.1516391551 0.9996\n",
      "I am working on tract number 2900 of 9129 tracts\n",
      "I am working on tract number 2920 of 9129 tracts\n",
      "I am working on tract number 2940 of 9129 tracts\n",
      "I am working on tract number 2960 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2965 5.0 2 452.4 0.1891 84104.9\n",
      "I am working on tract number 2980 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 2997 1 272455.31730628747 1.4144\n",
      "8 yoyos for tract,wedge,wedgePop,r= 2997 1 80257.93161220153 0.7072\n",
      "9 yoyos for tract,wedge,wedgePop,r= 2997 1 272502.0185005537 1.4157\n",
      "10 yoyos for tract,wedge,wedgePop,r= 2997 1 173574.15962589032 1.0614\n",
      "11 yoyos for tract,wedge,wedgePop,r= 2997 1 252934.12714688855 1.2385\n",
      "11 yoyos for tract,wedge,wedgePop,r= 2997 1 248483.4280983211 1.15\n",
      "11 yoyos for tract,wedge,wedgePop,r= 2997 1 211765.54087802535 1.1057\n",
      "I am working on tract number 3000 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3017 3 263071.6375231015 3.2503\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3017 3 123965.81742848147 1.6251\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3017 3 271693.87901874667 3.7152\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3017 3 151802.87346991844 2.6702\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3017 3 262403.4662884958 3.1927\n",
      "I am working on tract number 3020 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3033 9.0 2 452.4 0.5993 132164.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3033 10.0 2 452.4 0.7784 132164.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3033 11.0 2 452.4 1.0111 132164.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3034 5.0 2 90.0 0.3112 198778.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3034 6.0 2 90.0 0.3009 198778.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3034 7.0 2 90.0 0.2909 198778.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3034 8.0 2 90.0 0.2813 198778.7\n",
      "I am working on tract number 3040 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3041 3 267141.8033894454 3.7452\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3041 3 118424.34839069587 1.8726\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3041 3 267192.0678036308 3.8126\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3041 3 220927.2315947997 2.8426\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3041 3 129527.84252786584 2.3576\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3041 3 139439.00886168878 2.6001\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3041 3 157612.73095724444 2.7214\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3041 3 165778.3556110648 2.782\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3042 7.0 3 41.0 3.0253 192853.0\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3054 3 254924.44720706344 3.1612\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3054 3 116090.41120067556 1.5806\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3054 3 258405.11072273218 3.6034\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3054 3 142236.92160317593 2.592\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3054 3 254022.87797940528 3.0977\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3054 3 177037.26402657793 2.8449\n",
      "13 yoyos for tract,wedge,wedgePop,r= 3054 3 249808.13645322295 2.9713\n",
      "13 yoyos for tract,wedge,wedgePop,r= 3054 3 233069.9892983966 2.9081\n",
      "14 yoyos for tract,wedge,wedgePop,r= 3054 3 205515.30359369738 2.8765\n",
      "I am working on tract number 3060 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3078 4.0 0 122.2 0.2705 104258.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3078 5.0 0 122.2 0.4125 104258.9\n",
      "I am working on tract number 3080 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3091 8.0 2 452.4 0.9277 78555.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3092 3.0 1 90.0 0.2858 112723.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3097 6.0 2 262.3 0.5385 18813.9\n",
      "I am working on tract number 3100 of 9129 tracts\n",
      "I am working on tract number 3120 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3124 0 321394.3654649041 1.8214\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3124 0 157675.47561860588 0.9107\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3124 0 321330.76743663143 1.7987\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3124 0 272284.936097342 1.3547\n",
      "loop31.0, tr3124,wedgePops722533.13, 164876.3, 154593.4, 201587.8, 201475.6, Overedge?0, 1, 0, 0, ,Satisfied?0011,yoyo?9000 \n",
      "   targetWP, latest drx4 are tWP,dr, 201919.0,-0.222, 201919.0,0.9104, 201919.0,0.0012, 201919.0,0.0004\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3124 0 164876.31636878318 1.1327\n",
      "loop32.0, tr3124,wedgePops770435.76, 212778.9, 154593.4, 201587.8, 201475.6, Overedge?0, 1, 0, 0, ,Satisfied?0011,yoyo?10000 \n",
      "   targetWP, latest drx4 are tWP,dr, 201919.0,0.111, 201919.0,0.9104, 201919.0,0.0012, 201919.0,0.0004\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3124 0 212778.9454843871 1.2437\n",
      "loop33.0, tr3124,wedgePops725623.99, 167967.2, 154593.4, 201587.8, 201475.6, Overedge?0, 1, 0, 0, ,Satisfied?0011,yoyo?11000 \n",
      "   targetWP, latest drx4 are tWP,dr, 201919.0,-0.0555, 201919.0,0.9104, 201919.0,0.0012, 201919.0,0.0004\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3124 0 167967.16792417644 1.1882\n",
      "loop34.0, tr3124,wedgePops736620.82, 178964.0, 154593.4, 201587.8, 201475.6, Overedge?0, 1, 0, 0, ,Satisfied?0011,yoyo?12000 \n",
      "   targetWP, latest drx4 are tWP,dr, 201919.0,0.0278, 201919.0,0.9104, 201919.0,0.0012, 201919.0,0.0004\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3124 0 178964.00573641167 1.216\n",
      "loop35.0, tr3124,wedgePops751128.46, 193471.6, 154593.4, 201587.8, 201475.6, Overedge?0, 1, 0, 0, ,Satisfied?0011,yoyo?12000 \n",
      "   targetWP, latest drx4 are tWP,dr, 201919.0,0.0139, 201919.0,0.9104, 201919.0,0.0012, 201919.0,0.0004\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3124 0 193471.64347833206 1.2298\n",
      "loop36.0, tr3124,wedgePops759744.8, 202088.0, 154593.4, 201587.8, 201475.6, Overedge?0, 1, 0, 0, ,Satisfied?0011,yoyo?12000 \n",
      "   targetWP, latest drx4 are tWP,dr, 201919.0,0.0069, 201919.0,0.9104, 201919.0,0.0012, 201919.0,0.0004\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3128 3.0 0 90.0 0.2161 46307.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3128 4.0 0 90.0 0.5486 46307.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3130 2.0 3 90.0 0.6873 7668.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3131 2.0 3 90.0 0.4562 9359.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3132 3.0 2 90.0 0.5535 26723.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3137 2.0 0 90.0 0.5471 6479.5\n",
      "I am working on tract number 3140 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3142 5.0 3 47.9 0.4722 51726.8\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3142 3 551549.4959662902 1.773\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3142 3 63819.13203088695 0.8865\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3142 3 596908.617110612 1.9107\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3142 3 395972.35125829425 1.3986\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3142 3 370856.45270430663 1.1426\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3142 3 178437.22369440156 1.0145\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3142 3 335171.423649409 1.0786\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3142 3 288421.2278667421 1.0465\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3142 3 251352.97132811454 1.0305\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3142 3 214904.71690178761 1.0225\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3142 3 197107.6591821027 1.0185\n",
      "I am working on tract number 3160 of 9129 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 3165\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3178 4.0 0 102.3 0.2623 145142.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3178 5.0 0 102.3 0.3191 145142.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3178 6.0 0 102.3 0.3882 145142.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3178 7.0 0 102.3 0.4723 145142.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3179 5.0 0 90.0 0.6749 72669.5\n",
      "I am working on tract number 3180 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3190 5.0 0 90.0 1.2295 233610.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3190 6.0 0 90.0 1.0488 233610.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3191 4.0 0 90.0 0.2641 117181.3\n",
      "I am working on tract number 3200 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3219 2.0 3 90.0 0.5144 917672.2\n",
      "I am working on tract number 3220 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3226 2.0 3 90.0 0.1519 39808.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3226 3.0 3 90.0 0.422 39808.1\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3226 3 329968.1313323666 0.9465\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3226 3 133955.60199035885 0.4733\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3226 3 329896.29549355444 0.9404\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3228 6.0 0 126.0 0.2943 72927.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3228 7.0 0 126.0 0.5655 72927.4\n",
      "I am working on tract number 3240 of 9129 tracts\n",
      "I am working on tract number 3260 of 9129 tracts\n",
      "I am working on tract number 3280 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3292 5.0 1 90.0 0.7224 155167.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3292 11.0 0 92.4 0.3779 200284.9\n",
      "I am working on tract number 3300 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3303 2.0 0 90.0 0.1937 20784.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3305 2.0 0 90.0 0.1622 90638.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3305 3.0 0 90.0 0.2712 90638.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3305 4.0 0 90.0 0.4535 90638.2\n",
      "I am working on tract number 3320 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3320 0 249476.7654470619 1.6565\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3320 0 181289.44856983668 0.8282\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3320 0 249533.0549506376 1.667\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3320 0 240352.21367256247 1.2476\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3320 0 186348.12187048307 1.0379\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3320 0 192711.08085328573 1.1428\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3320 0 212152.13410862433 1.1952\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3320 0 228704.6626751471 1.2214\n",
      "loop31.0, tr3320,wedgePops761828.97, 220141.2, 104663.7, 218373.6, 218650.5, Overedge?0, 1, 0, 0, ,Satisfied?0011,yoyo?11011 \n",
      "   targetWP, latest drx4 are tWP,dr, 218562.2,-0.0131, 218562.2,0.9104, 218562.2,0.0054, 218562.2,-0.0068\n",
      "I am working on tract number 3340 of 9129 tracts\n",
      "I am working on tract number 3360 of 9129 tracts\n",
      "I am working on tract number 3380 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3382 3.0 1 90.0 0.6841 109469.9\n",
      "I am working on tract number 3400 of 9129 tracts\n",
      "I am working on tract number 3420 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3420 1 75751.78828230558 0.6483\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3420 1 599065.280731242 2.2447\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3420 1 397918.4678363078 1.4465\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3420 1 285315.92922312656 1.0474\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3420 1 92531.7791677046 0.8479\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3420 1 133838.03940974554 0.9476\n",
      "loop31.0, tr3420,wedgePops751911.2, 100602.2, 211624.4, 219708.4, 219976.2, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0902 \n",
      "   targetWP, latest drx4 are tWP,dr, 219916.0,0.9104, 219916.0,0.0499, 219916.0,0.0012, 219916.0,-0.0011\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3420 1 211624.38081595057 0.9975\n",
      "loop32.0, tr3420,wedgePops798765.9, 100602.2, 258479.1, 219708.4, 219976.2, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0902 \n",
      "   targetWP, latest drx4 are tWP,dr, 219916.0,0.9104, 219916.0,0.0249, 219916.0,0.0012, 219916.0,-0.0011\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3420 1 258479.0784859932 1.0225\n",
      "loop33.0, tr3420,wedgePops773879.1, 100602.2, 233592.3, 219708.4, 219976.2, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01002 \n",
      "   targetWP, latest drx4 are tWP,dr, 219916.0,0.9104, 219916.0,-0.0125, 219916.0,0.0012, 219916.0,-0.0011\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3420 1 233592.27382598768 1.01\n",
      "loop34.0, tr3420,wedgePops762366.0, 100602.2, 222079.2, 219708.4, 219976.2, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01002 \n",
      "   targetWP, latest drx4 are tWP,dr, 219916.0,0.9104, 219916.0,-0.0062, 219916.0,0.0012, 219916.0,-0.0011\n",
      "I am working on tract number 3440 of 9129 tracts\n",
      "I am working on tract number 3460 of 9129 tracts\n",
      "I am working on tract number 3480 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3499 0 201922.51566005172 1.0179\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3499 0 163279.33514195908 0.5089\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3499 0 201952.4687681905 1.0225\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3499 0 173229.2303004206 0.7657\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3499 0 200604.00906995835 0.8941\n",
      "I am working on tract number 3500 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3506 3 225512.57545623483 2.587\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3506 3 178012.75013962263 1.2935\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3506 3 224770.7824399277 2.4167\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3506 3 209338.57597771706 1.8551\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3506 3 179526.2631459433 1.5743\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3506 3 181822.58178877798 1.7147\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3506 3 184802.30312396164 1.7849\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3506 3 193535.70221493335 1.82\n",
      "I am working on tract number 3520 of 9129 tracts\n",
      "I am working on tract number 3540 of 9129 tracts\n",
      "I am working on tract number 3560 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3567 2 430464.0203247339 0.8662\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3567 2 39133.950241679384 0.4331\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3567 2 737535.6607052402 0.9371\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3567 2 58843.284560769214 0.6851\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3567 2 229536.518135876 0.8111\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3567 2 67763.63958213126 0.7481\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3567 2 118385.3159685493 0.7796\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3567 2 171987.18209473832 0.7954\n",
      "13 yoyos for tract,wedge,wedgePop,r= 3567 2 201868.4989984372 0.8033\n",
      "I am working on tract number 3580 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3585 10.0 3 40.5 4.1423 254689.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3585 11.0 3 40.5 4.0112 254689.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3585 12.0 3 40.5 3.8842 254689.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3585 18.0 3 40.5 4.093 254689.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3585 19.0 3 40.5 3.9635 254689.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3585 26.0 3 40.5 5.2678 254689.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3585 27.0 3 40.5 5.101 254689.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3585 28.0 3 40.5 4.9395 254689.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3585 29.0 3 40.5 4.7831 254689.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3585 30.0 3 40.5 4.6317 254689.9\n",
      "loop31.0, tr3585,wedgePops769925.83, 28196.6, 243506.8, 243532.5, 254689.9, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?0005 \n",
      "   targetWP, latest drx4 are tWP,dr, 244051.2,0.9104, 244051.2,0.0024, 244051.2,0.0031, 244051.2,-0.1467\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3585 31.0 3 40.5 4.485 254689.9\n",
      "loop32.0, tr3585,wedgePops769925.83, 28196.6, 243506.8, 243532.5, 254689.9, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?0005 \n",
      "   targetWP, latest drx4 are tWP,dr, 244051.2,0.9104, 244051.2,0.0024, 244051.2,0.0031, 244051.2,-0.142\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3585 32.0 3 40.5 4.343 254689.9\n",
      "loop33.0, tr3585,wedgePops769925.83, 28196.6, 243506.8, 243532.5, 254689.9, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?0005 \n",
      "   targetWP, latest drx4 are tWP,dr, 244051.2,0.9104, 244051.2,0.0024, 244051.2,0.0031, 244051.2,-0.1375\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3585 33.0 3 40.5 4.2055 254689.9\n",
      "loop34.0, tr3585,wedgePops769925.83, 28196.6, 243506.8, 243532.5, 254689.9, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?0005 \n",
      "   targetWP, latest drx4 are tWP,dr, 244051.2,0.9104, 244051.2,0.0024, 244051.2,0.0031, 244051.2,-0.1332\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3585 34.0 3 40.5 4.0724 254689.9\n",
      "loop35.0, tr3585,wedgePops769925.83, 28196.6, 243506.8, 243532.5, 254689.9, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?0005 \n",
      "   targetWP, latest drx4 are tWP,dr, 244051.2,0.9104, 244051.2,0.0024, 244051.2,0.0031, 244051.2,-0.1289\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3585 35.0 3 40.5 3.9434 254689.9\n",
      "loop36.0, tr3585,wedgePops769899.24, 28196.6, 243506.8, 243532.5, 254663.3, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?0005 \n",
      "   targetWP, latest drx4 are tWP,dr, 244051.2,0.9104, 244051.2,0.0024, 244051.2,0.0031, 244051.2,-0.1249\n",
      "loop37.0, tr3585,wedgePops620679.1, 28196.6, 243506.8, 243532.5, 105443.1, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?0005 \n",
      "   targetWP, latest drx4 are tWP,dr, 244051.2,0.9104, 244051.2,0.0024, 244051.2,0.0031, 244051.2,-1.9093\n",
      "loop38.0, tr3585,wedgePops748207.33, 28196.6, 243506.8, 243532.5, 232971.4, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?0006 \n",
      "   targetWP, latest drx4 are tWP,dr, 244051.2,0.9104, 244051.2,0.0024, 244051.2,0.0031, 244051.2,1.4448\n",
      "loop39.0, tr3585,wedgePops748355.34, 28196.6, 243506.8, 243532.5, 233119.4, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?0006 \n",
      "   targetWP, latest drx4 are tWP,dr, 244051.2,0.9104, 244051.2,0.0024, 244051.2,0.0031, 244051.2,0.0777\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 0 1.79866 27035.0829 28196.629 1\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 1 0.58377 240998.9868 243506.7926 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 2 0.42003 241647.4216 243532.5428 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 3 3.4318 232971.3637 233119.3732 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loop40.0, tr3585,wedgePops769925.83, 28196.6, 243506.8, 243532.5, 254689.9, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?0006 \n",
      "   targetWP, latest drx4 are tWP,dr, 244051.2,0.9104, 244051.2,0.0024, 244051.2,0.0031, 244051.2,2.9512\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 0 1.79866 27035.0829 28196.629 1\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 1 0.58377 240998.9868 243506.7926 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 2 0.42003 241647.4216 243532.5428 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 3 6.38301 233119.3732 254689.8631 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I looped 40 times on tract 3585, giving up w pop 769925.8274695887\n",
      "I am working on tract number 3600 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3606 2.0 0 90.0 0.2376 23012.2\n",
      "I am working on tract number 3620 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3628 0 250329.2047945304 0.9783\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3628 0 115875.59272114476 0.4892\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3628 0 316508.0623401012 1.1133\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3628 0 156489.99067606617 0.8012\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3628 0 228838.37837048364 0.9573\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3628 0 160426.8176601961 0.8793\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3628 0 184950.40507975905 0.9183\n",
      "13 yoyos for tract,wedge,wedgePop,r= 3628 0 208572.10325087694 0.9378\n",
      "13 yoyos for tract,wedge,wedgePop,r= 3628 0 197425.4827330331 0.928\n",
      "we have 2 non-opposing shorted wedges for tract no 3630\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3631 1 331177.6786984978 2.5411\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3631 1 151937.06580462604 1.2705\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3631 1 337731.8349861291 2.7888\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3631 1 324321.4277445394 2.0297\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3631 1 167110.94258265544 1.6501\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3631 1 260997.82142553473 1.8399\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3631 1 173679.086269888 1.745\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3631 1 215996.57859542576 1.7925\n",
      "13 yoyos for tract,wedge,wedgePop,r= 3631 1 239358.89448065672 1.8162\n",
      "loop31.0, tr3631,wedgePops756635.01, 122120.1, 230465.3, 233405.4, 170644.2, Overedge?1, 0, 0, 1, ,Satisfied?0010,yoyo?01300 \n",
      "   targetWP, latest drx4 are tWP,dr, 233793.1,0.057, 233793.1,-0.0119, 233793.1,0.0007, 233793.1,0.1217\n",
      "I am working on tract number 3640 of 9129 tracts\n",
      "I am working on tract number 3660 of 9129 tracts\n",
      "I am working on tract number 3680 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3686 2.0 2 90.0 0.1718 55824.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3686 6.0 0 120.5 0.6599 77024.4\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3686 3 229284.3824878893 1.0121\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3686 3 54079.415776905545 0.5061\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3686 3 408510.33625731396 1.5728\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3686 3 294557.7882344342 1.0394\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3686 3 60811.81895759769 0.7727\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3686 3 67679.79065313103 0.9061\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3686 3 95553.86033906353 0.9727\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3686 3 201933.38685728787 1.0061\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3686 3 134799.6981733787 0.9894\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3686 3 165688.28158891725 0.9977\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3686 3 183202.08418114216 1.0019\n",
      "I am working on tract number 3700 of 9129 tracts\n",
      "I am working on tract number 3720 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3731 2 417032.71729169734 2.0237\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3731 2 74660.23609998205 1.0118\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3731 2 431594.79976808483 2.1758\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3731 2 264343.56431434164 1.5938\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3731 2 241997.5400086863 1.3028\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3731 2 109044.62370972958 1.1573\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3731 2 184599.5209797675 1.2301\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3731 2 225389.74739249545 1.2665\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3731 2 208711.42408152283 1.2483\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3731 2 198166.85963454406 1.2392\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3732 1 247171.84134624642 1.9007\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3732 1 67220.54531599968 0.9503\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3732 1 248316.36532785214 2.3071\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3732 1 162750.56335420022 1.6287\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3732 1 247710.25250379712 1.9679\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3732 1 237145.9078562 1.7983\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3732 1 229572.6626403143 1.7135\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3732 1 206988.0199332452 1.6711\n",
      "loop31.0, tr3732,wedgePops753789.44, 189849.5, 184081.7, 189875.3, 189982.9, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?01120 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0005, 190087.6,-0.0212, 190087.6,0.0006, 190087.6,0.0002\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3732 1 184081.73033729088 1.6499\n",
      "loop32.0, tr3732,wedgePops764122.04, 189849.5, 194414.3, 189875.3, 189982.9, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?01220 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0005, 190087.6,0.0106, 190087.6,0.0006, 190087.6,0.0002\n",
      "I am working on tract number 3740 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3752 3.0 2 90.0 0.3613 109216.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3758 4.0 0 137.3 0.2994 41855.1\n",
      "I am working on tract number 3760 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3761 2.0 1 90.0 0.4632 211039.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3761 3.0 1 90.0 0.4278 211039.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3761 4.0 1 90.0 0.3951 211039.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3761 5.0 1 90.0 0.365 211039.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3761 6.0 1 90.0 0.3371 211039.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3761 7.0 1 90.0 0.3113 211039.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3761 8.0 1 90.0 0.2875 211039.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3761 9.0 1 90.0 0.2656 211039.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3772 5.0 1 90.0 0.3938 138736.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3774 8.0 2 452.4 0.1566 21927.8\n",
      "I am working on tract number 3780 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3780 2.0 1 90.0 0.2894 16068.6\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3799 1 209060.98895441426 2.246\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3799 1 149771.23991612432 1.123\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3799 1 209037.54057007172 2.2431\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3799 1 167252.94846173414 1.6831\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3799 1 173828.3594294132 1.9631\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3799 1 201554.75056139514 2.1031\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3799 1 176933.31508863144 2.0331\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3799 1 186084.0260937015 2.0681\n",
      "13 yoyos for tract,wedge,wedgePop,r= 3799 1 194187.11134405338 2.0856\n",
      "I am working on tract number 3800 of 9129 tracts\n",
      "I am working on tract number 3820 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3821 1 638115.3991627513 1.8888\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3821 1 113586.64256773947 0.9444\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3821 1 598947.9226346554 1.8172\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3821 1 450164.1042539501 1.3808\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3821 1 442171.0365342741 1.1626\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3821 1 339460.54412469896 1.0535\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3821 1 168356.69983583596 0.9989\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3821 1 245637.081452074 1.0262\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3821 1 201875.60353318587 1.0126\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3821 1 183764.04319299653 1.0058\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3824 6.0 1 90.0 0.6079 166643.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3824 7.0 1 90.0 0.6699 166643.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3824 8.0 1 90.0 0.7383 166643.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3824 9.0 1 90.0 0.8136 166643.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3824 10.0 1 90.0 0.8966 166643.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3826 11.0 2 452.4 0.2123 173736.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3833 10.0 3 -272.4 0.2308 177847.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3833 11.0 3 -272.4 0.2425 177847.2\n",
      "I am working on tract number 3840 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3841 4.0 2 241.7 0.5044 5381.5\n",
      "I am working on tract number 3860 of 9129 tracts\n",
      "I am working on tract number 3880 of 9129 tracts\n",
      "I am working on tract number 3900 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3902 9.0 0 90.0 0.3559 187469.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3917 5.0 0 96.0 0.4864 196756.5\n",
      "I am working on tract number 3920 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3921 5.0 2 90.0 0.2403 167117.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3921 6.0 2 90.0 0.2643 167117.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3921 7.0 2 90.0 0.2906 167117.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3921 13.0 2 452.4 0.2791 162049.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3921 14.0 2 452.4 0.3139 162049.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3921 15.0 2 452.4 0.353 162049.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3921 16.0 2 452.4 0.397 162049.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3921 17.0 2 452.4 0.4465 162049.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3921 18.0 2 452.4 0.5021 162049.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3921 19.0 2 452.4 0.5647 162049.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3921 20.0 2 452.4 0.635 162049.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3921 21.0 2 452.4 0.7141 162049.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3921 22.0 2 452.4 0.8031 162049.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3921 23.0 2 452.4 0.9032 162049.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3927 3.0 2 90.0 1.059 224087.4\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3927 2 201093.9128570007 0.5983\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3927 2 146.51489769120235 0.2992\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3927 2 207718.03102816458 0.6331\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3927 2 11777.91915657607 0.4661\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3927 2 119623.96108972326 0.5496\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3933 1 577263.8913282242 1.571\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3933 1 94896.89101214195 0.7855\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3933 1 611603.2251889698 1.5863\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3933 1 301114.72985040257 1.1859\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3933 1 210976.33280907135 0.9857\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3933 1 109884.9788863289 0.8856\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3933 1 172148.81868566803 0.9357\n",
      "loop31.0, tr3933,wedgePops745721.44, 142207.0, 190760.5, 206369.2, 206384.8, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01031 \n",
      "   targetWP, latest drx4 are tWP,dr, 206047.8,0.1774, 206047.8,0.025, 206047.8,-0.0015, 206047.8,-0.0034\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3933 1 190760.527775167 0.9607\n",
      "loop32.0, tr3933,wedgePops753447.5, 142207.0, 198486.6, 206369.2, 206384.8, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01031 \n",
      "   targetWP, latest drx4 are tWP,dr, 206047.8,0.1774, 206047.8,0.0125, 206047.8,-0.0015, 206047.8,-0.0034\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3933 1 198486.58035403004 0.9732\n",
      "loop33.0, tr3933,wedgePops759046.78, 142207.0, 204085.9, 206369.2, 206384.8, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01031 \n",
      "   targetWP, latest drx4 are tWP,dr, 206047.8,0.1774, 206047.8,0.0063, 206047.8,-0.0015, 206047.8,-0.0034\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3938 1 602574.6461839768 1.613\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3938 1 90148.26431644364 0.8065\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3938 1 607800.1773831805 1.6601\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3938 1 295269.22604790446 1.2333\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3938 1 277655.9344771682 1.0199\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3938 1 172228.0908321439 0.9132\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3938 1 223513.049970827 0.9665\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3938 1 191305.3595230793 0.9399\n",
      "loop31.0, tr3938,wedgePops753577.08, 129089.8, 204003.1, 210394.5, 210089.7, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01220 \n",
      "   targetWP, latest drx4 are tWP,dr, 210420.2,0.2121, 210420.2,0.0133, 210420.2,0.0245, 210420.2,0.0158\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3938 1 204003.07615908908 0.9532\n",
      "loop32.0, tr3938,wedgePops761975.74, 129089.8, 212401.7, 210394.5, 210089.7, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01220 \n",
      "   targetWP, latest drx4 are tWP,dr, 210420.2,0.2121, 210420.2,0.0067, 210420.2,0.0245, 210420.2,0.0158\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3939 1 279715.50070330466 0.9959\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3939 1 78855.29954418697 0.4979\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3939 1 285304.53287218127 1.2373\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3939 1 134312.15353089815 0.8676\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3939 1 281783.97774038836 1.0524\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3939 1 245581.73059489497 0.96\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3939 1 189951.4317522613 0.9138\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3939 1 208445.35674787767 0.9369\n",
      "13 yoyos for tract,wedge,wedgePop,r= 3939 1 224901.1859387394 0.9485\n",
      "I am working on tract number 3940 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3940 2 543860.8414026388 2.0042\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3940 2 131339.51223174966 1.0021\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3940 2 447369.2998475582 1.9564\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3940 2 243415.1816581198 1.4793\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3940 2 260565.04625449493 1.7179\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3940 2 291662.7158508609 1.8371\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3940 2 263353.7235928266 1.7775\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3946 3.0 0 143.4 1.0135 3375.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3947 4.0 0 138.4 0.2104 23240.4\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3956 0 195577.2275351216 1.1357\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3956 0 49734.79404478351 0.5678\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3956 0 392178.36128042045 1.2101\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3956 0 93443.25284848287 0.889\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3956 0 120940.97796271667 1.0495\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3956 0 181752.45900409814 1.1298\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3956 0 299943.3262771335 1.17\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3956 0 239658.5827116918 1.1499\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3956 0 207103.86268041725 1.1398\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3959 3 289705.7825855548 3.0507\n",
      "loop31.0, tr3959,wedgePops680777.14, 189905.4, 110867.6, 189643.9, 190360.3, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0301 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0004, 190087.6,-0.8592, 190087.6,0.0013, 190087.6,-0.0005\n",
      "loop32.0, tr3959,wedgePops686342.09, 189905.4, 116432.5, 189643.9, 190360.3, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0401 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0004, 190087.6,0.3705, 190087.6,0.0013, 190087.6,-0.0005\n",
      "loop33.0, tr3959,wedgePops880638.62, 189905.4, 310729.0, 189643.9, 190360.3, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0401 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0004, 190087.6,1.7184, 190087.6,0.0013, 190087.6,-0.0005\n",
      "loop34.0, tr3959,wedgePops857195.7, 189905.4, 287286.1, 189643.9, 190360.3, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0501 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0004, 190087.6,-0.7124, 190087.6,0.0013, 190087.6,-0.0005\n",
      "loop35.0, tr3959,wedgePops683557.52, 189905.4, 113647.9, 189643.9, 190360.3, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0501 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0004, 190087.6,-1.1179, 190087.6,0.0013, 190087.6,-0.0005\n",
      "loop36.0, tr3959,wedgePops837874.92, 189905.4, 267965.3, 189643.9, 190360.3, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0601 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0004, 190087.6,0.468, 190087.6,0.0013, 190087.6,-0.0005\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3959 1 267965.3458489739 1.5859\n",
      "loop37.0, tr3959,wedgePops680318.89, 189905.4, 110409.3, 189643.9, 190360.3, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0701 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0004, 190087.6,-0.793, 190087.6,0.0013, 190087.6,-0.0005\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3959 1 110409.32230503578 0.793\n",
      "loop38.0, tr3959,wedgePops857316.25, 189905.4, 287406.7, 189643.9, 190360.3, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0801 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0004, 190087.6,1.4741, 190087.6,0.0013, 190087.6,-0.0005\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3959 1 287406.67758412834 2.267\n",
      "loop39.0, tr3959,wedgePops790447.12, 189905.4, 220537.5, 189643.9, 190360.3, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0901 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0004, 190087.6,-0.737, 190087.6,0.0013, 190087.6,-0.0005\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 0 0.18975 189104.5769 189905.4005 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 1 1.52999 287406.6776 220537.5457 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 2 0.21524 188208.6662 189643.8829 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 3 0.13956 192082.6026 190360.287 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9 yoyos for tract,wedge,wedgePop,r= 3959 1 220537.54568971146 1.53\n",
      "loop40.0, tr3959,wedgePops684309.31, 189905.4, 114399.7, 189643.9, 190360.3, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?0901 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0004, 190087.6,-0.3685, 190087.6,0.0013, 190087.6,-0.0005\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 0 0.18975 189104.5769 189905.4005 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 1 1.16147 220537.5457 114399.7364 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 2 0.21524 188208.6662 189643.8829 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 3 0.13956 192082.6026 190360.287 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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khOb+K81sNuG7pIOpPzulfpxz7kDGaj0A18jmk4AtzrmtzrnjwP3A5e2MWUQCIBHWCc3L/Hv/okV9+GZWaGargX3AEufci6nlN5tZFTCHRlr4QBSoyvh7V2pZY/u4xsxWmNmK/fv3t+IQRMSP0qWZdXXhKs2Ml/q3NLNFCd85V5fquikFJplZeWr5jc65GDAPuK6RTa2xtzvFPuY65yY65yaWlJS0KHgR8a94SEfN7Ffs39LMVlXpOOfeBZYC0xu8dB8wq5FNdgGxjL9LAf+dBRHJuvRDSH6f5zUX4j7tzmpJlU6JmRWnfu8GTAM2mtnIjNUuAzY2svlLwEgzS5hZZ+CzwF/aHbWI+F56mIGtPuzLzrVEWSSwLfwhwFNmtoZkAl/inFsI/NjM1qWWXwxcD2BmETOrBHDO1ZLs6nkU2AA84Jxbn4PjEBGfGVzSn65duoSzhR+LUr13v+9KM4uaW8E5twaY0MjyxrpwcM7tBioy/q4EKtsRo4gEkJklnzoNYws/FuHEiRNU7d7LiHiZ1+HU05O2IpIziVjUl33ZuZYeWmKrz45dCV9EciYei4SyNNOvN6yV8EUkZxJl0VCWZvbt04s+vXr6rjtLCV9EciZemqzU8VtLN9eS9y+ivjtuJXwRyZn0MANhLc1UC19EQmPQgH4qzfRRaaYSvojkTEFBgUozd/tn1EwlfBHJqXgsEtoWPvhrEhglfBHJqUQsnKNm+nFCcyV8EcmpeCzC8Zoadr8RrmHP06WZfhpTRwlfRHLKjy3dfEiXZvrpuJXwRSSn0qNmbvNRSzdf4jF/jZqphC8iOZUeNdNPLd18SZRF2bVnH8drarwOBVDCF5EcKygoIF46JJyVOqXJ0ky/TGiuhC8iOZcoi4azFt9nE5o3Ox6+BI9zjtd3vMVDj6xnQeU6qna/B8CUs8uY/+urPI5OwigRi/LEM8upq6ujsLDQ63DyJpG+f+GT7iwl/IA7crSGpc9vZUHlWhY/9VqT644ersnhxRuZpZmxyGCvw8mbvn16+6o0Uwk/IJxz7Kh+l4ceWc/8RWvZXvVOk+uX9O/BrIpyrphRzpgRAykosDxFKvJhiYynTsOU8M2MeMw/E5or4fvQ0WO1LFu+jQWV6/jrkg3Nrn/OpDizK8ZyyQUj6d2zax4iFGmd+tLMqmrO++hZHkeTX4lYlJfXNf/vOB+U8D3knGPXnvf4f4++yoLKtWze9laT6xf36casinJmzShn7OjBarVLYIR7QvMIf1nyNMdraujcqZOnsSjh58nxmjqeW7GD+YvW8tAj65tdf/JZMWZVjGXGhaPo26dbHiIUyZ10aaZfujbyKRGL1pdmjojHPI1FCT8Hdr9xgL8s2cD8RWvZsLnpqd169ujM7IqxXFFRzvjTh1BYqEpZ6ZgSZVE2b9vpdRh5l9mdpYQfYDW1dbzw8k4WVK5jQeU6TpxwTa5/9rgosyvGMvOiUfTv2yNPUYr4Q7w0EsrSzGFl/pnQXAm/hd548yB/XfIqCyrXsWZD00/Nde1SxKyKcmbPHMtZ5VGKitRqF0mURUNbmtm7Zw9fPHylhN9Abe0JVq7dxfxF65i/aC3Ha5oew3v86UOYVVHOpdPGMHBAzzxFKRI8J7s2wleamSjzx4TmoU74b759iIVPbGRB5TpeXtv0p29hoTG7YiyzZpYzaXyMTkXh+Uoqkg0na/HDV5oZL42wav1Gr8MIR8KvqzvBqvW7WVCZbLUfPtL0yHVnnDaIWRXlXHbx6QwZ2CtPUYp0bMnSzM6+aOnmW6Isyl8f/5vnpZkdLuG/894RKp/cyPxFa1m+elez618xo5xPzxzL5LPL6NxJrXaRXEmWZvrnqdN88ktpZodK+Ff80x94cVVVo6+NGjaA2TPHcvklpxMd3CfPkYkIJPvxX9/RfEOso0nfv9i+a7cSfrZcfP5pvLiqisv+bgyzZ47lnElxunTuUIcoEmiJWJQnn30ptKWZXn+76VDZ8NqrPsq1V320Vds89Mh+9r15nC9dFc1RVCKSlh41c8++NykdMsjrcPImXZrp9f2LZgvEzayrmS03s1fMbL2Z3ZRafquZbTSzNWb2kJkVn2L7r6a2W2dmfzQzX43udd23X+MHP9/udRgioZCeEGRryPrx06WZXtfit+SJoGPAVOfcmcB4YLqZTQaWAOXOuXHAa8ANDTc0syjwFWCic64cKAQ+m6XYRSRg4qWpvuwQVurESyOeH3ezCd8lHUz92Sn145xzjznnalPLXwBKT/EWRUA3MysCugO+/D996HDTD1iJSPsNGTiArl06e97S9UKiLErVnjc8ndC8Rc/8m1mhma0G9gFLnHMvNljli8Dihts556qB24CdwB7gPefcY6fYxzVmtsLMVuzfv78Vh9A+k8/qDcDy1Qfytk+RsCooKGBoNNwTmlftfsOzGFqU8J1zdc658SRb8ZPMrDz9mpndCNQC8xpuZ2Z9gcuBBBABephZo5OqOufmOucmOucmlpTkbyq+Cz/WF4Cnnmt6BikRyQ4/9GV7wQ8TmrdqVC/n3LvAUmA6gJn9A3ApMMc519hQkdOAbc65/c65GuBB4GPtCTjbLphSDMCTSvgieRGPRdixaw91deHqRk1PaO7lt5uWVOmUpCtwzKwbySS+0cymA98ALnPOHT7F5juByWbW3cwMuAjwx1xfKaOHJ4cp3rbzqMeRiIRDIhatL80Mk37FfZKjZnpYodSSFv4Q4CkzWwO8RLIPfyFwB9ALWGJmq83sVwBmFjGzSoBUX/984GVgbWp/c7N/GG1XVKRpAkXyKXPUzDBJT2i+fZd3x93sg1fOuTXAhEaWjzjF+ruBioy/vwd8rx0xikgHUj9q5s5qzp30odTSoSViUVav3+TZ/jUzRwaVZorkXro008uWrlfisYinpZlK+Kg0UySf0qWZXo8r44X0qJlelWYq4dOxSjOdc6zduIrv/vTfOGPqIKITO9f/HDj4ntfhiQDhLc3MnNDcCx1q8LS2umBKMf9xxw6efO4dfuB1MK1w8ND7VD71EAsq7+OZ5U82ue4VM66ke1dNnC7+EI9FQj1qplelmUr4+L800znHhi1rWVB5Hwsq57H/raa/DibKRjCrYg6zZlxJWTSRpyhFWi6zNDNMo2b2K+5Drx7dPevOUsLHX6WZR44e5pGlDzN/0TyWPt/oKBQfMOPCy5lVMYepH59Bl85d8hChSPtllmaGKeHXT2ju0Q1rJXwPbd62gfmV85i/aB579zX9iR+LxJk9cw5XzLiSYWUj8xShSG6EuTQzXhrhlVdf82TfSvgNHDpcR4/u2e1TPHrsKEuWLWT+ont5fFlls+tPO7eC2TOvYto5M+nWtVtWYxHxgzCXZibKoix8YpknE5or4ad8dEJvXlx1gJdeOcAFU/q2+X22VW1hQarVXrV7e5PrDh4YZfbMOcyumMPIxJg271MkaMJcmhmPnRw1c/jQU40qnxtK+Clf+MwQXlx1oMUPXx07fownn13Mgsp5LH7q4WbXv/BjlzCr4kouOf8yundTtYxIPBYJ3fAKcLI7a3vVbiV8r3xi2gBGPdCdkYkPd6HsrN7GgsX3MX/RPLZXbWnyfQb0G8jsmVcxq+JKxowYS3LMOBFpKFEWZenzKzhx4gQFBeF5JGiYh8MkK+FnSJR14olnFzN/0b38dcn8Ztc/Z9JUZlVcScWFn6Jnj155iFCk44iXRjh2PFmaGR080Otw8iZdmulFLX5oE3713ioeeuSPLKicx2tbmx6xubh3X2bNvIrZFXMYO3qCWu0iWZA5oXmYEr6XE5qHJuHX1NYQn9x83/nks85lVsUcZl50BX16Fec+MJGQOtmXHc7SzDUbNud9v6FJ+EWFHzzUnj16JZ9GrZjDWeWT1GoXybMhAwfQpXOncN64LYuy6Mll1NTW0qkof2k4NAnfzNjxwmGK8nhyReTUCgoKGFoaYXtIB1Grq0uWZqZv4uZDeG6Ng5K9iM8kQl6ame/nEEKV8EXEX+KxKDt27ebEiRNeh5JX9ROa71LCF5GQSMROlmaGSf++xalRM/P77UYJX0Q8E4959xCSl05OaK4WvoiERP1TpyEcUycRi6qFLyLhkS7NDOOomckJzfdSU1ubt30q4YuIZ9KlmaFs4ZdF60sz80UJX0Q8FS8NaWlm6cknjfNFCV9EPJUoC2lpZll6mkclfBEJicxRM8Okf99ieua5NFMJX0Q8lfBwfHgvmRmJPJdmKuGLiKfST52G8cZtPM+lmUr4IuKpyKCS0JZmJvJcmqmELyKeKigooCy0E5rntzRTCV9EPJeIRT2Z8s9rw2L5Lc1sNuGbWVczW25mr5jZejO7KbX8VjPbaGZrzOwhMys+xfbFZjY/te4GM5uS5WMQkYBLlEXZUb0ndKWZ8Vh+SzNb0sI/Bkx1zp0JjAemm9lkYAlQ7pwbB7wG3HCK7X8BPOKcGw2cCTQ9gayIhE68NMLRY8dDV5o5oF+yNDNf326aTfgu6WDqz06pH+ece8w5l77T8AJQ2nBbM+sNnAfcnXqv4865d7MRuIh0HGEvzfRTCx8zKzSz1cA+YIlz7sUGq3wRWNzIpsOA/cA9ZrbKzH5rZo3OJG5m15jZCjNbsX///pYfgYgEXv2EICHsx4/HonkbWqJFCd85V+ecG0+yFT/JzMrTr5nZjUAtMK+RTYuAs4C7nHMTgEPAN0+xj7nOuYnOuYklJSWtOwoRCbTIoOS/+e//7FesXLuBI0ePehxR/iRiEap256c0s1WTvDrn3jWzpcB0YJ2Z/QNwKXCRc841sskuYFfGN4L5nCLhi0h4FRQk255Hjh7jsi9cT2FhASPjZZSPHsG4MSMZO3okZ5w2nB7du3kcafalSzN37Xmjfq7bXGk24ZtZCVCTSvbdgGnALWY2HfgGcL5z7nBj2zrn9ppZlZmNcs5tAi4CXs1i/CLSQWx7fhH733qHtRs3s3bjFtZs2MzTL6xk/qLHgWR/9/ChpfUfAGNHj6R81HB69Wy0lzgwhmVMaO55wgeGAL8zs0KSXUAPOOcWmtkWoAuwxMwAXnDOXWtmEeC3zrmK1PZfBuaZWWdgK/CFrB+FiARe506diA4eSHTwQKZf8PH65Xv3v8WaDa+xLvUh8NzKNTy4+Mn61xNlUcaNHsnY0SMYO2Yk5aNGUNy7lxeH0CbxPN6/aDbhO+fWABMaWT7iFOvvBioy/l4NTGx7iCISZoNL+jO4ZAoXn3fyEZ70N4E1GzazbtMWVqx5lYcfW1r/+tDokIzuoBGMHX0a/Yp7exB989Klmfmo1GlVH76IiB+U9O/L1I9PYurHJ9Uve/vd9z7QHbRu4xYWPbGs/vXSIYNSyT/5ITBuzEgG9OvrRfgfYGbESyP+aOGLiARBv+I+nD95IudPPtmh8O6B91m3aQtrNyS/DazdtIXFTz1b//rggQM+0B00dvRIBpf0z3vsibIoazduzvl+lPBFpMMq7t2Lcz4ygXM+crJX+sDBQ6zf9HryvsCm5LeBJcteIF1oOLB/v/ruoHGjR1I+egSRQSWk7lXmRLw0wuInn6GmtpZORblLy0r4IhIqvXv2YMrZ45hy9rj6ZYcOH2H9a6/X3xdYu2EzS59fUT+2T/++feorg9LdQaVDBmXtQyBRFqW2ri7npZlK+CISej26d2PS+HImja9/ppQjR4+y/rWt9dVBazdt5q7fP0BtXR0AxX16MXZU6p5A6uZwvDTSpg+BzCeNlfBFRPKsW9euTBx3OhPHnV6/7Oix42zcsi1VHZT8NvCb+x6sf0q2d88elKduDKe7g4aVResfLDuVREYt/oUf+0jOjkkJX0Skhbp26cz4M0Yx/oxR9cuO19Sw6fXtGdVBm/mfBx7m2PEaIPntoXzU8PouoXFjRjJ8aCmFhYX17zGgXzE9unfL+axfSvgiIu3QuVOn+mR+5SdnAFBTW8trW3dkdAdt4d4HKzl67BgA3bp24YzThjNuzEjKUx8CZZHBOZ/1yxofAsdbEydOdCtWrPA6DBGRrKmtreP1HVX1HwBrUw+NHT5ycqC4YWWlLHvwv9v0/ma20jnX5EOuauGLiORBUVEho4bHGTU8zqcv/TsA6urq2FZVXd8dNLR0SG5jyOm7i4jIKRUWFjIiXsaIeBmfmj415/vTJOYiIiGhhC8iEhJK+CIiIaGELyISEkr4IiIhoYQvIhISSvgiIiGhhC8iEhK+HFrBzPYDOxosHgC86UE4baV4cyto8ULwYla8uZXteIc650qaWsGXCb8xZraiuXEi/ETx5lbQ4oXgxax4c8uLeNWlIyISEkr4IiIhEaSEP9frAFpJ8eZW0OKF4MWseHMr7/EGpg9fRETaJ0gtfBERaQclfBGRkMh7wjezT5vZejM7YWYTM5b3N7OnzOygmd2RsbyXma3O+HnTzH7eyPv+nZmtNLO1qf9OzXhtqZltyniPgV7Hm1r3BjPbkortkozlZ6eOY4uZ/ZeZWUvjbUvMqdc6m9lcM3vNzDaa2axG3ndOg2M7YWbjU6/l7Ry3It64mR3JiOlXGa+1+RznMF5fXMMtjTe1np+u4WbPkc+u4ZbEm91r2DmX1x9gDDAKWApMzFjeAzgHuBa4o4ntVwLnNbJ8AhBJ/V4OVGe89oF9+STe04FXgC5AAngdKEy9thyYAhiwGJiR65iBm4AfpX4vAAY0s4+xwFavznFL4gXiwLpT7LPN5ziH8frmGm5hvH67hlt1jnxwDTe7v2xfw3mf4tA5twGg4YeRc+4Q8IyZjTjVtmY2EhgILGvkfVdl/Lke6GpmXZxzx/wYL3A5cH8qvm1mtgWYZGbbgd7OuedT7/F74JMk/4fmMuYvAqNT652g+ScAPwf8saUxNSVP8dYzsyG04xznKl6fXcMtOb9+u4Zby+truM3aeg0HrQ//c8CfXOrjrQmzgFUN/qHck/pK9J3Wfr1sh6bijQJVGX/vSi2Lpn5vuDxnzKw49esPzexlM/uzmQ1qZrPP8OF/LHk5x62MN2Fmq8zsaTM7N7Usr+e4jefXs2u4FfH65hrO0Jpz5Nk13Mr9Ze0azknCN7PHzWxdIz+Xt/OtP0szn8hmdgZwC/CljMVznHNjgXNTP3/vg3gb+5/rmlj+wY2zG3MRUAo865w7C3geuO1UK5vZR4HDzrl1GYvzeY5bGu8eoMw5NwH4GnCfmfWmBefY4/Pr9TXc0nj9dA1DM+eowb69voZbGm+br+HG5KRLxzk3LdvvaWZnAkXOuZVNrFMKPAR83jn3ekY81an/vm9m9wGTgN97HO8uIJbxdymwO7W8tJHlH5DlmN8CDpM8dwB/Bq5uYv0PfZDl+Ry3KN5U6/hY6veVZvY6cBotOMdenV+fXMMtjddP13Cz56gBr6/hFsXbnmu4MUHq0mmyvy31NXQRcINz7tmM5UVmNiD1eyfgUmBdo2+SXc31D/4F+KyZdTGzBDASWO6c2wO8b2aTU1/xPg88nMtAU11OfwUuSC26CHi1sXXNrAD4NHB/xrK8nuOWxmtmJWZWmPp9GMlzvDXf57gV8Rbjg2u4FdeDb67h1pwjP1zDLd1f1q/hltyBzuYP8CmSn07HgDeARzNe2w68DRxMrXN6xmtbgdEN3usy4Aep378NHAJWZ/wMJHmXfCWwhuSNsF+QqiTwMt7U3zeSrGzYRMYddmBi6n/+68AdpJ6IzmXMwFDgb6nz9ATJr5GNxXwB8EKD/eX9HLckXpL94OtJVpK8DHwiG+c4h/H65hpuxfXgi2u4qXPUSMwX4PE13NJ4yfI1rKEVRERCIkhdOiIi0g5K+CIiIaGELyISEkr4IiIhoYQvIhISSvgiIiGhhC8iEhL/H2pBW4/4lFJFAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I looped 40 times on tract 3959, giving up w pop 684309.3067206993\n",
      "I am working on tract number 3960 of 9129 tracts\n",
      "I am working on tract number 3980 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3984 0 297175.6264959929 1.7344\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3984 0 99174.52690987231 0.8672\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3984 0 292019.5641914641 1.6771\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3984 0 130631.41675409663 1.2721\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3984 0 253245.21183843378 1.4746\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3984 0 204831.09567777556 1.3734\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3984 0 152731.80209893372 1.3228\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3984 0 174785.90688965167 1.3481\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 3996 13.0 3 55.3 3.0517 224818.3\n",
      "7 yoyos for tract,wedge,wedgePop,r= 3996 3 197937.47986337636 2.7715\n",
      "8 yoyos for tract,wedge,wedgePop,r= 3996 3 87455.47771103146 1.3857\n",
      "9 yoyos for tract,wedge,wedgePop,r= 3996 3 217768.21460424538 2.816\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3996 3 108796.78946955485 2.1009\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3996 3 117934.92746223268 2.4585\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3996 3 136786.90152909997 2.6373\n",
      "10 yoyos for tract,wedge,wedgePop,r= 3996 3 151663.43353306616 2.7266\n",
      "11 yoyos for tract,wedge,wedgePop,r= 3996 3 197806.83000397767 2.7713\n",
      "12 yoyos for tract,wedge,wedgePop,r= 3996 3 173955.96964350916 2.749\n",
      "I am working on tract number 4000 of 9129 tracts\n",
      "I am working on tract number 4020 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4023 3 197687.22569078195 0.7357\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4023 3 41757.215343670105 0.3678\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4023 3 285448.6932576675 0.7752\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4023 3 90418.29076656839 0.5715\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4023 3 104625.29357602369 0.6734\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4023 3 176838.02014814384 0.7243\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4023 3 220037.68269579666 0.7498\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4023 3 199815.728622303 0.737\n",
      "I am working on tract number 4040 of 9129 tracts\n",
      "I am working on tract number 4060 of 9129 tracts\n",
      "I am working on tract number 4080 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4092 3 333796.9080552722 1.7161\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4092 3 135445.89519208603 0.8581\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4092 3 325342.7774728673 1.6717\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4092 3 289823.5240227087 1.2649\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4092 3 247446.3078459976 1.0615\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4092 3 151807.41497233737 0.9598\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4092 3 210013.5821573519 1.0106\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4092 3 179966.74905244022 0.9852\n",
      "13 yoyos for tract,wedge,wedgePop,r= 4092 3 194525.79335234794 0.9979\n",
      "I am working on tract number 4100 of 9129 tracts\n",
      "I am working on tract number 4120 of 9129 tracts\n",
      "I am working on tract number 4140 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4141 4.0 1 90.0 0.2835 123947.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4148 2.0 1 90.0 0.179 59385.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4148 3.0 1 90.0 0.3908 59385.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4150 9.0 0 97.8 0.2554 150810.2\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4156 1 259065.12769546662 0.6567\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4156 1 158606.90734271638 0.3284\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4156 1 244108.71559598716 0.6213\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4156 1 232061.80779054257 0.4748\n",
      "I am working on tract number 4160 of 9129 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 4169\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4171 7.0 0 108.2 1.8202 198171.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4171 8.0 0 108.2 1.7639 198171.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4175 5.0 2 452.4 0.1722 20998.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4178 3.0 1 90.0 0.4603 63100.7\n",
      "I am working on tract number 4180 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4183 3.0 0 90.0 0.2607 104526.0\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4191 2 1348906.2731695718 1.7178\n",
      "loop31.0, tr4191,wedgePops746042.26, 314102.2, 51460.2, 52557.0, 327922.9, Overedge?0, 1, 1, 0, ,Satisfied?0001,yoyo?4005 \n",
      "   targetWP, latest drx4 are tWP,dr, 328166.6,0.2911, 328166.6,0.9104, 328166.6,-0.8589, 328166.6,0.002\n",
      "loop32.0, tr4191,wedgePops768576.93, 336636.9, 51460.2, 52557.0, 327922.9, Overedge?0, 1, 1, 0, ,Satisfied?0001,yoyo?4005 \n",
      "   targetWP, latest drx4 are tWP,dr, 328166.6,0.1311, 328166.6,0.9104, 328166.6,-0.8589, 328166.6,0.002\n",
      "loop33.0, tr4191,wedgePops767711.66, 335771.6, 51460.2, 52557.0, 327922.9, Overedge?0, 1, 1, 0, ,Satisfied?0001,yoyo?5005 \n",
      "   targetWP, latest drx4 are tWP,dr, 328166.6,-0.0386, 328166.6,0.9104, 328166.6,-0.8589, 328166.6,0.002\n",
      "loop34.0, tr4191,wedgePops725279.15, 293339.1, 51460.2, 52557.0, 327922.9, Overedge?0, 1, 1, 0, ,Satisfied?0001,yoyo?5005 \n",
      "   targetWP, latest drx4 are tWP,dr, 328166.6,-0.3033, 328166.6,0.9104, 328166.6,-0.8589, 328166.6,0.002\n",
      "loop35.0, tr4191,wedgePops742250.52, 310310.5, 51460.2, 52557.0, 327922.9, Overedge?0, 1, 1, 0, ,Satisfied?0001,yoyo?6005 \n",
      "   targetWP, latest drx4 are tWP,dr, 328166.6,0.2019, 328166.6,0.9104, 328166.6,-0.8589, 328166.6,0.002\n",
      "loop36.0, tr4191,wedgePops768867.21, 336927.2, 51460.2, 52557.0, 327922.9, Overedge?0, 1, 1, 0, ,Satisfied?0001,yoyo?6005 \n",
      "   targetWP, latest drx4 are tWP,dr, 328166.6,0.153, 328166.6,0.9104, 328166.6,-0.8589, 328166.6,0.002\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4191 0 336927.19470312056 2.0224\n",
      "loop37.0, tr4191,wedgePops621961.25, 190021.2, 51460.2, 52557.0, 327922.9, Overedge?0, 1, 1, 0, ,Satisfied?0001,yoyo?7005 \n",
      "   targetWP, latest drx4 are tWP,dr, 328166.6,-1.0112, 328166.6,0.9104, 328166.6,-0.8589, 328166.6,0.002\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4191 0 190021.23933606653 1.0112\n",
      "loop38.0, tr4191,wedgePops768722.67, 336782.7, 51460.2, 52557.0, 327922.9, Overedge?0, 1, 1, 0, ,Satisfied?0001,yoyo?8005 \n",
      "   targetWP, latest drx4 are tWP,dr, 328166.6,1.0047, 328166.6,0.9104, 328166.6,-0.8589, 328166.6,0.002\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4191 0 336782.66456437914 2.0158\n",
      "loop39.0, tr4191,wedgePops719699.16, 287759.1, 51460.2, 52557.0, 327922.9, Overedge?0, 1, 1, 0, ,Satisfied?0001,yoyo?9005 \n",
      "   targetWP, latest drx4 are tWP,dr, 328166.6,-0.5023, 328166.6,0.9104, 328166.6,-0.8589, 328166.6,0.002\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 0 1.51351 336782.6646 287759.1447 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 1 3.06393 46396.8486 51460.1503 1\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 2 0.85889 1348906.2732 52556.9841 1\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 3 0.93979 326787.0997 327922.876 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10 yoyos for tract,wedge,wedgePop,r= 4191 0 287759.14469348406 1.5135\n",
      "loop40.0, tr4191,wedgePops732966.77, 301026.8, 51460.2, 52557.0, 327922.9, Overedge?0, 1, 1, 0, ,Satisfied?0001,yoyo?10005 \n",
      "   targetWP, latest drx4 are tWP,dr, 328166.6,0.2512, 328166.6,0.9104, 328166.6,-0.8589, 328166.6,0.002\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 0 1.76468 287759.1447 301026.7557 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 1 3.06393 46396.8486 51460.1503 1\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 2 0.85889 1348906.2732 52556.9841 1\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 3 0.93979 326787.0997 327922.876 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I looped 40 times on tract 4191, giving up w pop 732966.7659974482\n",
      "I am working on tract number 4200 of 9129 tracts\n",
      "I am working on tract number 4220 of 9129 tracts\n",
      "I am working on tract number 4240 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4245 0 438441.57821931725 0.6555\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4245 0 98269.59130207688 0.3278\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4245 0 448037.3321546246 0.7093\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4245 0 381671.8877333086 0.5185\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4245 0 203895.2504601614 0.4231\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4245 0 122554.14239322543 0.3755\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4245 0 158739.43740359473 0.3993\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4245 0 179066.21791875767 0.4112\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4251 3 284802.6763900502 0.4397\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4251 3 11309.17129327677 0.2198\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4251 3 287168.7797668736 0.4527\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4251 3 85139.01582780489 0.3363\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4251 3 249566.76832207094 0.3945\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4251 3 177791.2078082998 0.3654\n",
      "13 yoyos for tract,wedge,wedgePop,r= 4251 3 221435.191823581 0.3799\n",
      "13 yoyos for tract,wedge,wedgePop,r= 4251 3 202657.40363153085 0.3727\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4258 2 248152.49098184082 0.633\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4258 2 104997.23371469488 0.3165\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4258 2 264847.9696429503 0.6815\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4258 2 126153.80225008805 0.499\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4258 2 212713.48256873875 0.5902\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4258 2 159288.24591555164 0.5446\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4258 2 186491.99604280392 0.5674\n",
      "13 yoyos for tract,wedge,wedgePop,r= 4258 2 199806.87332788378 0.5788\n",
      "I am working on tract number 4260 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4264 2.0 2 90.0 0.1819 117252.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4264 3.0 2 90.0 0.2565 117252.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4264 4.0 2 90.0 0.3616 117252.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4264 5.0 2 90.0 0.5099 117252.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4264 8.0 0 117.5 0.2066 99957.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4264 9.0 0 117.5 0.324 99957.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4264 10.0 0 117.5 0.5082 99957.2\n",
      "I am working on tract number 4280 of 9129 tracts\n",
      "I am working on tract number 4300 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4306 6.0 2 452.4 0.2407 45469.3\n",
      "I am working on tract number 4320 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4322 0 236681.13395698444 3.9701\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4322 0 174856.863597064 1.9851\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4322 0 236681.13395698197 4.0096\n",
      "need to widen edge circle beyond 0.0007173893917074305 for tract (x,y)=( -122.26587270472696 37.50778342357442\n",
      "need to widen edge circle beyond 0.0007891283308781737 for tract (x,y)=( -122.26587270472696 37.50778342357442\n",
      "need to widen edge circle beyond 0.0008680411639659911 for tract (x,y)=( -122.26587270472696 37.50778342357442\n",
      "need to widen edge circle beyond 0.0009548452803625903 for tract (x,y)=( -122.26587270472696 37.50778342357442\n",
      "need to widen edge circle beyond 0.0010503298083988494 for tract (x,y)=( -122.26587270472696 37.50778342357442\n",
      "need to widen edge circle beyond 0.0011553627892387345 for tract (x,y)=( -122.26587270472696 37.50778342357442\n",
      "need to widen edge circle beyond 0.0012708990681626082 for tract (x,y)=( -122.26587270472696 37.50778342357442\n",
      "need to widen edge circle beyond 0.001397988974978869 for tract (x,y)=( -122.26587270472696 37.50778342357442\n",
      "need to widen edge circle beyond 0.001537787872476756 for tract (x,y)=( -122.26587270472696 37.50778342357442\n",
      "need to widen edge circle beyond 0.0016915666597244318 for tract (x,y)=( -122.26587270472696 37.50778342357442\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "I am working on tract number 4340 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4340 10.0 3 50.7 0.2711 166800.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4340 11.0 3 50.7 0.3187 166800.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4340 12.0 3 50.7 0.3746 166800.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4340 13.0 3 50.7 0.4404 166800.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4340 14.0 3 50.7 0.5176 166800.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4340 15.0 3 50.7 0.6085 166800.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4340 16.0 3 50.7 0.7152 166800.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4346 4.0 0 133.9 0.2221 27251.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4348 2.0 1 90.0 0.3543 190804.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4348 3.0 1 90.0 0.3533 190804.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4348 4.0 1 90.0 0.3523 190804.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4348 5.0 1 90.0 0.3513 190804.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4348 6.0 1 90.0 0.3503 190804.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4350 5.0 0 83.4 0.2491 110387.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4356 6.0 3 46.6 0.2374 118299.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4356 7.0 3 46.6 0.3327 118299.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4359 4.0 0 114.4 0.4093 284131.6\n",
      "I am working on tract number 4360 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4362 1 287555.8519232301 2.1471\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4362 1 92265.31337107046 1.0735\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4362 1 287556.3765497779 2.1473\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4362 1 124694.11709530748 1.6104\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4362 1 270388.02918893413 1.8789\n",
      "loop31.0, tr4362,wedgePops747290.66, 189987.2, 177571.4, 189767.1, 189964.9, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?11120 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,-0.0028, 190087.6,-0.1342, 190087.6,0.0018, 190087.6,0.0002\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4362 1 177571.43388566788 1.7447\n",
      "loop32.0, tr4362,wedgePops807584.33, 189987.2, 237865.1, 189767.1, 189964.9, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?11220 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,-0.0028, 190087.6,0.0671, 190087.6,0.0018, 190087.6,0.0002\n",
      "13 yoyos for tract,wedge,wedgePop,r= 4362 1 237865.10902015597 1.8118\n",
      "loop33.0, tr4362,wedgePops775289.94, 189987.2, 205570.7, 189767.1, 189964.9, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?11320 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,-0.0028, 190087.6,-0.0336, 190087.6,0.0018, 190087.6,0.0002\n",
      "13 yoyos for tract,wedge,wedgePop,r= 4362 1 205570.71290660524 1.7782\n",
      "loop34.0, tr4362,wedgePops762766.02, 189987.2, 193046.8, 189767.1, 189964.9, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?11320 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,-0.0028, 190087.6,-0.0168, 190087.6,0.0018, 190087.6,0.0002\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4368 11.0 1 59.9 1.045 169947.6\n",
      "I am working on tract number 4380 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4382 3 257721.50597975805 2.992\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4382 3 119157.18073012985 1.496\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4382 3 264988.5501923811 3.0206\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4382 3 142513.41446880106 2.2583\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4382 3 156993.94604349727 2.6395\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4382 3 180216.87685341688 2.8301\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4386 3 236567.2851045447 3.5358\n",
      "loop31.0, tr4386,wedgePops2165910.15, 144391.0, 1606451.4, 210462.7, 204605.0, Overedge?1, 0, 0, 0, ,Satisfied?0000,yoyo?0110 \n",
      "   targetWP, latest drx4 are tWP,dr, 205319.8,0.7468, 205319.8,0.7076, 205319.8,-0.0128, 205319.8,0.0011\n",
      "loop32.0, tr4386,wedgePops1604633.46, 144391.0, 1048658.8, 206410.3, 205173.3, Overedge?1, 0, 0, 0, ,Satisfied?0000,yoyo?0210 \n",
      "   targetWP, latest drx4 are tWP,dr, 205319.8,0.7468, 205319.8,-0.5334, 205319.8,-0.003, 205319.8,0.0002\n",
      "loop33.0, tr4386,wedgePops641052.32, 144391.0, 85908.5, 205579.5, 205173.3, Overedge?1, 0, 0, 0, ,Satisfied?0001,yoyo?0210 \n",
      "   targetWP, latest drx4 are tWP,dr, 205319.8,0.7468, 205319.8,-0.3026, 205319.8,-0.0007, 205319.8,0.0002\n",
      "loop34.0, tr4386,wedgePops672410.69, 144391.0, 117266.9, 205579.5, 205173.3, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0310 \n",
      "   targetWP, latest drx4 are tWP,dr, 205319.8,0.7468, 205319.8,0.0415, 205319.8,-0.0007, 205319.8,0.0002\n",
      "loop35.0, tr4386,wedgePops711958.05, 144391.0, 156814.2, 205579.5, 205173.3, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0310 \n",
      "   targetWP, latest drx4 are tWP,dr, 205319.8,0.7468, 205319.8,0.0768, 205319.8,-0.0007, 205319.8,0.0002\n",
      "loop36.0, tr4386,wedgePops775500.54, 144391.0, 220356.7, 205579.5, 205173.3, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0310 \n",
      "   targetWP, latest drx4 are tWP,dr, 205319.8,0.7468, 205319.8,0.0627, 205319.8,-0.0007, 205319.8,0.0002\n",
      "loop37.0, tr4386,wedgePops726152.94, 144391.0, 171009.1, 205579.5, 205173.3, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0410 \n",
      "   targetWP, latest drx4 are tWP,dr, 205319.8,0.7468, 205319.8,-0.0113, 205319.8,-0.0007, 205319.8,0.0002\n",
      "loop38.0, tr4386,wedgePops746751.06, 144391.0, 191607.2, 205579.5, 205173.3, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0510 \n",
      "   targetWP, latest drx4 are tWP,dr, 205319.8,0.7468, 205319.8,0.0063, 205319.8,-0.0007, 205319.8,0.0002\n",
      "loop39.0, tr4386,wedgePops761451.36, 144391.0, 206307.5, 205579.5, 205173.3, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0510 \n",
      "   targetWP, latest drx4 are tWP,dr, 205319.8,0.7468, 205319.8,0.0033, 205319.8,-0.0007, 205319.8,0.0002\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 0 3.9378 142341.2464 144391.0368 1\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 1 0.48189 191607.2438 206307.5487 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 2 0.50232 206410.3459 205579.4671 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 3 0.27906 204605.0036 205173.3086 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I am working on tract number 4400 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4403 3 524490.080423038 0.8689\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4403 3 146511.204293133 0.4345\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4403 3 584154.3440928778 1.043\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4403 3 339271.085444432 0.7387\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4403 3 159803.37703355684 0.5866\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4403 3 194248.2441097844 0.6627\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4403 3 167934.49024193874 0.6246\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4403 3 175472.15220089033 0.6436\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4403 3 182533.2691510515 0.6532\n",
      "we have 2 non-opposing shorted wedges for tract no 4411\n",
      "I am working on tract number 4420 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4420 3 2465773.6564304014 2.1386\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4424 17.0 3 37.3 7.1492 190759.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4424 18.0 3 37.3 7.1303 190759.3\n",
      "I am working on tract number 4440 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4443 0 197883.77599262237 0.5977\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4443 0 27815.538013721263 0.2989\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4443 0 288984.5766484996 0.6796\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4443 0 38518.64921294115 0.4892\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4443 0 158319.82946084422 0.5844\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4443 0 237622.34910357336 0.632\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4443 0 218181.99223545822 0.6082\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4443 0 194194.49226825437 0.5963\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4443 0 176944.64130669815 0.5904\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4443 0 185770.99314977103 0.5933\n",
      "I am working on tract number 4460 of 9129 tracts\n",
      "I am working on tract number 4480 of 9129 tracts\n",
      "I am working on tract number 4500 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4502 3 551099.4249905003 2.5754\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4502 3 35203.769370309135 1.2877\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4502 3 464395.4345428745 2.5589\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4502 3 58504.280339189456 1.9233\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4502 3 102522.4777435062 2.2411\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4502 3 198148.17612809927 2.4\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4502 3 213594.31446252347 2.4795\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4502 3 293905.16343647667 2.5192\n",
      "I am working on tract number 4520 of 9129 tracts\n",
      "I am working on tract number 4540 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4551 12.0 1 66.4 2.5315 181755.9\n",
      "we have 2 non-opposing shorted wedges for tract no 4555\n",
      "I am working on tract number 4560 of 9129 tracts\n",
      "I am working on tract number 4580 of 9129 tracts\n",
      "I am working on tract number 4600 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4606 3 326959.23320963245 1.8064\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4606 3 99093.34403574088 0.9032\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4606 3 327229.287319336 1.8083\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4606 3 158597.7242055838 1.3558\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4606 3 282361.63461666263 1.582\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4606 3 265220.50175036315 1.4689\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4606 3 224495.27348448237 1.4123\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4611 1 254029.33960705675 3.4549\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4611 1 106919.85435093785 1.7275\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4611 1 251276.27321950946 3.4357\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4611 1 130080.04823254148 2.5816\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4611 1 237521.42881981723 3.0086\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4611 1 168742.54057550337 2.7951\n",
      "13 yoyos for tract,wedge,wedgePop,r= 4611 1 234422.70436903895 2.9018\n",
      "13 yoyos for tract,wedge,wedgePop,r= 4611 1 210987.06969895953 2.8485\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4612 3 303575.7205374526 3.7726\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4612 3 153459.11252746466 1.8863\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4612 3 303091.5541261253 3.7321\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4612 3 197368.10550345754 2.8092\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4612 3 297197.90251700394 3.2707\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4612 3 273781.6866629891 3.0399\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4612 3 210292.60520489572 2.9246\n",
      "13 yoyos for tract,wedge,wedgePop,r= 4612 3 252839.53408432505 2.9823\n",
      "14 yoyos for tract,wedge,wedgePop,r= 4612 3 226114.94530880565 2.9534\n",
      "I am working on tract number 4620 of 9129 tracts\n",
      "I am working on tract number 4640 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4652 6.0 0 139.5 0.5453 145139.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4652 7.0 0 139.5 0.6634 145139.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4652 8.0 0 139.5 0.8071 145139.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4652 9.0 0 139.5 0.9819 145139.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4658 2.0 1 90.0 0.2638 273638.9\n",
      "I am working on tract number 4660 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4676 21.0 1 50.4 3.8165 220576.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4676 22.0 1 50.4 3.7249 220576.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4676 23.0 1 50.4 3.6356 220576.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4676 24.0 1 50.4 3.5483 220576.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4676 25.0 1 50.4 3.4632 220576.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4676 26.0 1 50.4 3.3801 220576.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4676 27.0 1 50.4 3.2991 220576.9\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4676 1 220008.70519922988 2.8151\n",
      "loop31.0, tr4676,wedgePops578738.36, 119616.1, 32486.1, 213304.7, 213331.4, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0711 \n",
      "   targetWP, latest drx4 are tWP,dr, 213578.1,0.3032, 213578.1,-1.4075, 213578.1,0.0004, 213578.1,0.0003\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4676 1 32486.050828652893 1.4075\n",
      "loop32.0, tr4676,wedgePops766829.23, 119616.1, 220576.9, 213304.7, 213331.4, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0811 \n",
      "   targetWP, latest drx4 are tWP,dr, 213578.1,0.3032, 213578.1,2.158, 213578.1,0.0004, 213578.1,0.0003\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4676 1 220576.91237076535 3.5655\n",
      "loop33.0, tr4676,wedgePops749456.54, 119616.1, 203204.2, 213304.7, 213331.4, Overedge?1, 1, 0, 0, ,Satisfied?0011,yoyo?0000 \n",
      "   targetWP, latest drx4 are tWP,dr, 218765.0,0.3032, 218765.0,-1.079, 218765.0,0.0004, 218765.0,0.0003\n",
      "loop34.0, tr4676,wedgePops758263.17, 119616.1, 203204.2, 217673.8, 217769.0, Overedge?1, 1, 0, 0, ,Satisfied?0000,yoyo?0000 \n",
      "   targetWP, latest drx4 are tWP,dr, 218765.0,0.3032, 218765.0,-1.079, 218765.0,0.0016, 218765.0,0.0011\n",
      "I am working on tract number 4680 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4682 7.0 0 83.6 0.3413 218841.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4682 8.0 0 83.6 0.3065 218841.1\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4683 2 273006.72972523636 2.5452\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4683 2 84896.93831587044 1.2726\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4683 2 273003.85298529314 2.5441\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4683 2 116721.63698985134 1.9083\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4683 2 264882.9234974491 2.2262\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4683 2 243845.12850125122 2.0673\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4683 2 185041.55367397505 1.9878\n",
      "13 yoyos for tract,wedge,wedgePop,r= 4683 2 215095.69217402098 2.0275\n",
      "13 yoyos for tract,wedge,wedgePop,r= 4683 2 200320.0761120265 2.0077\n",
      "13 yoyos for tract,wedge,wedgePop,r= 4683 2 192962.08127169072 1.9977\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4688 4.0 0 123.7 0.5244 5397.7\n",
      "I am working on tract number 4700 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4710 2.0 1 90.0 0.3301 50146.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4710 6.0 0 107.6 0.3127 59848.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4713 4.0 0 121.0 0.3335 18242.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4715 2.0 3 90.0 0.2258 24674.3\n",
      "I am working on tract number 4720 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4723 2.0 3 90.0 0.29 41536.1\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4727 1 269511.9904150508 0.5255\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4727 1 5720.612040424661 0.2627\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4727 1 275689.9539069244 0.5391\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4727 1 53207.06493375919 0.4009\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4727 1 134783.63048856723 0.47\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4727 1 212484.4564019069 0.5046\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4727 1 262218.57748686074 0.5218\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4727 1 238130.42517898837 0.5132\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4729 2.0 0 90.0 0.4285 45703.7\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4729 1 376677.1686993778 0.6373\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4729 1 89477.82668634539 0.3187\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4729 1 404839.4308557183 0.8705\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4729 1 283661.8318614845 0.5946\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4729 1 94704.3763072333 0.4566\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4729 1 150587.73331490534 0.5256\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4729 1 213085.54017764493 0.5601\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4729 1 244141.9241825824 0.5773\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4729 1 262219.72663962655 0.5859\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4729 1 252730.5895967367 0.5816\n",
      "I am working on tract number 4740 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4749 0 211711.9301158277 1.9128\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4749 0 129297.68964671102 0.9564\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4749 0 211374.1225763404 1.8866\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4749 0 148892.5431701254 1.4215\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4749 0 195329.60134783236 1.654\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4749 0 167004.61443577462 1.5377\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4749 0 180588.9060035735 1.5959\n",
      "I am working on tract number 4760 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4767 4.0 3 40.7 0.2079 107285.7\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4770 2 360896.77243303694 1.4602\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4770 2 78353.53644254961 0.7301\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4770 2 506801.43832382164 1.921\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4770 2 312693.22157676495 1.3256\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4770 2 85350.48480592805 1.0278\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4770 2 159117.47568154632 1.1767\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4770 2 219216.6391631591 1.2511\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4770 2 183928.1634869008 1.2139\n",
      "13 yoyos for tract,wedge,wedgePop,r= 4770 2 203141.20711945952 1.2325\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4773 2.0 2 90.0 0.2191 37879.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4773 5.0 0 94.5 0.2142 39944.5\n",
      "I am working on tract number 4780 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4793 3.0 1 90.0 0.1748 98630.6\n",
      "I am working on tract number 4800 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4800 3 367052.89754375623 1.9589\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4800 3 109568.46734801363 0.9795\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4800 3 568874.8332235633 2.0245\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4800 3 147920.66404866823 1.502\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4800 3 187973.87607595936 1.7632\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4800 3 214255.5858235984 1.8938\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4800 3 368207.3164793964 1.9592\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4800 3 237343.82868131404 1.9265\n",
      "13 yoyos for tract,wedge,wedgePop,r= 4800 3 300618.4646821734 1.9428\n",
      "14 yoyos for tract,wedge,wedgePop,r= 4800 3 269932.15261682123 1.9347\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4802 6.0 3 90.0 2.2416 124717.1\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4804 2 617697.210993329 1.601\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4804 2 21618.13840422232 0.8005\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4804 2 667135.5942971644 1.7188\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4804 2 438541.10657607974 1.2596\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4804 2 164660.83021541702 1.0301\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4804 2 273980.82529740134 1.1449\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4804 2 230058.85494744556 1.0875\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4804 2 196966.2783493028 1.0588\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4804 2 182207.39681437696 1.0444\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4813 0 215243.30590836823 1.7167\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4813 0 123827.43855586331 0.8584\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4813 0 290154.52434897283 2.478\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4813 0 177634.09531648614 1.6682\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4813 0 289141.1047808513 2.0731\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4813 0 255937.72493923508 1.8706\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4813 0 234728.91347148365 1.7694\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4813 0 217094.3921896328 1.7188\n",
      "I am working on tract number 4820 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4822 6.0 2 90.0 0.3094 174938.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4822 7.0 2 90.0 0.3291 174938.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4822 8.0 2 90.0 0.35 174938.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4822 9.0 2 90.0 0.3723 174938.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4822 10.0 2 90.0 0.3959 174938.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4822 11.0 2 90.0 0.4211 174938.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4822 12.0 2 90.0 0.4479 174938.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4822 13.0 2 90.0 0.4764 174938.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4822 14.0 2 90.0 0.5067 174938.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4822 15.0 2 90.0 0.5389 174938.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4822 16.0 2 90.0 0.5732 174938.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4822 17.0 2 90.0 0.6096 174938.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4827 3.0 1 90.0 0.2537 68443.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4827 8.0 3 89.8 0.327 143123.2\n",
      "need to widen edge circle beyond 0.0008635685204039509 for tract (x,y)=( -122.25938839133346 37.56746114650713\n",
      "need to widen edge circle beyond 0.0009499253724443461 for tract (x,y)=( -122.25938839133346 37.56746114650713\n",
      "need to widen edge circle beyond 0.0010449179096887807 for tract (x,y)=( -122.25938839133346 37.56746114650713\n",
      "need to widen edge circle beyond 0.001149409700657659 for tract (x,y)=( -122.25938839133346 37.56746114650713\n",
      "need to widen edge circle beyond 0.001264350670723425 for tract (x,y)=( -122.25938839133346 37.56746114650713\n",
      "need to widen edge circle beyond 0.0013907857377957675 for tract (x,y)=( -122.25938839133346 37.56746114650713\n",
      "need to widen edge circle beyond 0.0015298643115753444 for tract (x,y)=( -122.25938839133346 37.56746114650713\n",
      "need to widen edge circle beyond 0.001682850742732879 for tract (x,y)=( -122.25938839133346 37.56746114650713\n",
      "need to widen edge circle beyond 0.001851135817006167 for tract (x,y)=( -122.25938839133346 37.56746114650713\n",
      "need to widen edge circle beyond 0.0020362493987067837 for tract (x,y)=( -122.25938839133346 37.56746114650713\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "need to widen edge circle beyond 0.001047266381499181 for tract (x,y)=( -122.24951517451345 37.55764748539822\n",
      "need to widen edge circle beyond 0.0011519930196490992 for tract (x,y)=( -122.24951517451345 37.55764748539822\n",
      "need to widen edge circle beyond 0.0012671923216140092 for tract (x,y)=( -122.24951517451345 37.55764748539822\n",
      "need to widen edge circle beyond 0.0013939115537754101 for tract (x,y)=( -122.24951517451345 37.55764748539822\n",
      "need to widen edge circle beyond 0.0015333027091529513 for tract (x,y)=( -122.24951517451345 37.55764748539822\n",
      "need to widen edge circle beyond 0.0016866329800682466 for tract (x,y)=( -122.24951517451345 37.55764748539822\n",
      "need to widen edge circle beyond 0.0018552962780750714 for tract (x,y)=( -122.24951517451345 37.55764748539822\n",
      "need to widen edge circle beyond 0.0020408259058825786 for tract (x,y)=( -122.24951517451345 37.55764748539822\n",
      "need to widen edge circle beyond 0.0022449084964708366 for tract (x,y)=( -122.24951517451345 37.55764748539822\n",
      "need to widen edge circle beyond 0.0024693993461179205 for tract (x,y)=( -122.24951517451345 37.55764748539822\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "need to widen edge circle beyond 0.0008492384883546415 for tract (x,y)=( -122.284736358118 37.546123800057\n",
      "need to widen edge circle beyond 0.0009341623371901058 for tract (x,y)=( -122.284736358118 37.546123800057\n",
      "need to widen edge circle beyond 0.0010275785709091166 for tract (x,y)=( -122.284736358118 37.546123800057\n",
      "need to widen edge circle beyond 0.0011303364280000282 for tract (x,y)=( -122.284736358118 37.546123800057\n",
      "need to widen edge circle beyond 0.0012433700708000311 for tract (x,y)=( -122.284736358118 37.546123800057\n",
      "need to widen edge circle beyond 0.0013677070778800344 for tract (x,y)=( -122.284736358118 37.546123800057\n",
      "need to widen edge circle beyond 0.001504477785668038 for tract (x,y)=( -122.284736358118 37.546123800057\n",
      "need to widen edge circle beyond 0.0016549255642348418 for tract (x,y)=( -122.284736358118 37.546123800057\n",
      "need to widen edge circle beyond 0.001820418120658326 for tract (x,y)=( -122.284736358118 37.546123800057\n",
      "need to widen edge circle beyond 0.002002459932724159 for tract (x,y)=( -122.284736358118 37.546123800057\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "need to widen edge circle beyond 0.0007835998418147109 for tract (x,y)=( -122.28887784105797 37.537386852517095\n",
      "need to widen edge circle beyond 0.0008619598259961821 for tract (x,y)=( -122.28887784105797 37.537386852517095\n",
      "need to widen edge circle beyond 0.0009481558085958003 for tract (x,y)=( -122.28887784105797 37.537386852517095\n",
      "need to widen edge circle beyond 0.0010429713894553804 for tract (x,y)=( -122.28887784105797 37.537386852517095\n",
      "need to widen edge circle beyond 0.0011472685284009186 for tract (x,y)=( -122.28887784105797 37.537386852517095\n",
      "need to widen edge circle beyond 0.0012619953812410107 for tract (x,y)=( -122.28887784105797 37.537386852517095\n",
      "need to widen edge circle beyond 0.001388194919365112 for tract (x,y)=( -122.28887784105797 37.537386852517095\n",
      "need to widen edge circle beyond 0.0015270144113016233 for tract (x,y)=( -122.28887784105797 37.537386852517095\n",
      "need to widen edge circle beyond 0.0016797158524317858 for tract (x,y)=( -122.28887784105797 37.537386852517095\n",
      "need to widen edge circle beyond 0.0018476874376749644 for tract (x,y)=( -122.28887784105797 37.537386852517095\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "I am working on tract number 4840 of 9129 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 4847\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4848 4.0 3 38.6 0.1791 31905.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4849 4.0 3 39.0 0.1865 23811.9\n",
      "we have 2 non-opposing shorted wedges for tract no 4850\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4851 1 359786.6730394899 1.7959\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4851 1 203719.69125073377 0.898\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4851 1 375774.83532689494 1.9801\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4851 1 209096.35532369898 1.439\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4851 1 300298.28942151554 1.7096\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4851 1 363708.48004948377 1.8449\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4851 1 357609.34060709656 1.7772\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4851 1 340505.8269306172 1.7434\n",
      "need to widen edge circle beyond 0.0009433156818747487 for tract (x,y)=( -122.27357858520936 37.526875299620635\n",
      "need to widen edge circle beyond 0.0010376472500622238 for tract (x,y)=( -122.27357858520936 37.526875299620635\n",
      "need to widen edge circle beyond 0.0011414119750684463 for tract (x,y)=( -122.27357858520936 37.526875299620635\n",
      "need to widen edge circle beyond 0.001255553172575291 for tract (x,y)=( -122.27357858520936 37.526875299620635\n",
      "need to widen edge circle beyond 0.0013811084898328202 for tract (x,y)=( -122.27357858520936 37.526875299620635\n",
      "need to widen edge circle beyond 0.0015192193388161024 for tract (x,y)=( -122.27357858520936 37.526875299620635\n",
      "need to widen edge circle beyond 0.0016711412726977128 for tract (x,y)=( -122.27357858520936 37.526875299620635\n",
      "need to widen edge circle beyond 0.0018382553999674843 for tract (x,y)=( -122.27357858520936 37.526875299620635\n",
      "need to widen edge circle beyond 0.002022080939964233 for tract (x,y)=( -122.27357858520936 37.526875299620635\n",
      "need to widen edge circle beyond 0.0022242890339606567 for tract (x,y)=( -122.27357858520936 37.526875299620635\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "need to widen edge circle beyond 0.0008988169355587551 for tract (x,y)=( -122.28831845916723 37.520824390642616\n",
      "need to widen edge circle beyond 0.0009886986291146307 for tract (x,y)=( -122.28831845916723 37.520824390642616\n",
      "need to widen edge circle beyond 0.0010875684920260938 for tract (x,y)=( -122.28831845916723 37.520824390642616\n",
      "need to widen edge circle beyond 0.0011963253412287033 for tract (x,y)=( -122.28831845916723 37.520824390642616\n",
      "need to widen edge circle beyond 0.0013159578753515738 for tract (x,y)=( -122.28831845916723 37.520824390642616\n",
      "need to widen edge circle beyond 0.0014475536628867313 for tract (x,y)=( -122.28831845916723 37.520824390642616\n",
      "need to widen edge circle beyond 0.0015923090291754046 for tract (x,y)=( -122.28831845916723 37.520824390642616\n",
      "need to widen edge circle beyond 0.0017515399320929452 for tract (x,y)=( -122.28831845916723 37.520824390642616\n",
      "need to widen edge circle beyond 0.00192669392530224 for tract (x,y)=( -122.28831845916723 37.520824390642616\n",
      "need to widen edge circle beyond 0.002119363317832464 for tract (x,y)=( -122.28831845916723 37.520824390642616\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "I am working on tract number 4860 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4869 1 411177.1871825176 2.0237\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4869 1 236170.31094153767 1.0118\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4869 1 415939.5473721103 2.5629\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4869 1 304750.5191840292 1.7874\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4869 1 415284.8429360996 2.1751\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4869 1 404250.8340543886 1.9812\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4869 1 395080.2903292332 1.8843\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4869 1 351439.6229454079 1.8358\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4869 1 327287.2305344588 1.8116\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4869 1 318464.7643418092 1.7995\n",
      "loop31.0, tr4869,wedgePops760867.37, 92521.0, 323108.8, 323135.5, 22102.1, Overedge?1, 0, 0, 1, ,Satisfied?0010,yoyo?01210 \n",
      "   targetWP, latest drx4 are tWP,dr, 322863.6,0.048, 322863.6,0.0061, 322863.6,-0.0011, 322863.6,0.2152\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4873 1 393854.87008606835 2.6041\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4873 1 213785.99721176675 1.3021\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4873 1 400468.4783118349 2.8611\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4873 1 387279.75126996776 2.0816\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4873 1 229418.61724020375 1.6918\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4873 1 321614.4585167778 1.8867\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4873 1 236002.68799015222 1.7893\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4873 1 274727.5906374047 1.838\n",
      "loop31.0, tr4873,wedgePops764346.75, 114744.1, 300484.9, 296036.1, 53081.6, Overedge?1, 0, 0, 1, ,Satisfied?0010,yoyo?01200 \n",
      "   targetWP, latest drx4 are tWP,dr, 296262.3,0.2179, 296262.3,0.0244, 296262.3,0.0002, 296262.3,0.22\n",
      "13 yoyos for tract,wedge,wedgePop,r= 4873 1 300484.93833097373 1.8623\n",
      "loop32.0, tr4873,wedgePops753837.9, 114744.1, 289976.1, 296036.1, 53081.6, Overedge?1, 0, 0, 1, ,Satisfied?0010,yoyo?01300 \n",
      "   targetWP, latest drx4 are tWP,dr, 296262.3,0.2179, 296262.3,-0.0122, 296262.3,0.0002, 296262.3,0.22\n",
      "14 yoyos for tract,wedge,wedgePop,r= 4873 1 289976.0870725552 1.8502\n",
      "loop33.0, tr4873,wedgePops759756.1, 114744.1, 295894.3, 296036.1, 53081.6, Overedge?1, 0, 0, 1, ,Satisfied?0010,yoyo?01400 \n",
      "   targetWP, latest drx4 are tWP,dr, 296262.3,0.2179, 296262.3,0.0061, 296262.3,0.0002, 296262.3,0.22\n",
      "I am working on tract number 4880 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4880 5.0 2 452.4 0.1924 55825.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4880 6.0 2 452.4 0.4364 55825.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4888 9.0 3 80.2 0.3766 168805.4\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4889 1 375684.44602373126 2.9512\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4889 1 193404.000433339 1.4756\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4889 1 368793.9389609088 2.697\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4889 1 358784.99870968476 2.0863\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4889 1 208650.5902502498 1.781\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4889 1 320591.6383371548 1.9336\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4889 1 248419.89071141317 1.8573\n",
      "13 yoyos for tract,wedge,wedgePop,r= 4889 1 284588.44769237516 1.8955\n",
      "13 yoyos for tract,wedge,wedgePop,r= 4889 1 270297.0521336272 1.8764\n",
      "13 yoyos for tract,wedge,wedgePop,r= 4889 1 260295.4951731034 1.8668\n",
      "loop31.0, tr4889,wedgePops761723.38, 127680.5, 254459.7, 252705.2, 126878.1, Overedge?1, 0, 0, 1, ,Satisfied?0010,yoyo?01300 \n",
      "   targetWP, latest drx4 are tWP,dr, 252895.9,0.1467, 252895.9,-0.0048, 252895.9,0.0002, 252895.9,0.2218\n",
      "we have 2 non-opposing shorted wedges for tract no 4890\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4893 12.0 0 91.0 0.4752 187435.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4893 13.0 0 91.0 0.4802 187435.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4893 14.0 0 91.0 0.4853 187435.4\n",
      "I am working on tract number 4900 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4907 3 198767.0066913235 0.6301\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4907 3 4400.793147337739 0.315\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4907 3 471712.78575018526 0.6559\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4907 3 49906.23474578862 0.4855\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4907 3 66478.95682863708 0.5707\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4907 3 125443.93792061103 0.6133\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4907 3 235310.9802169909 0.6346\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4907 3 163689.71115034987 0.624\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4913 5.0 1 45.9 1.05 209920.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4913 6.0 1 45.9 1.1347 209920.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4913 7.0 1 45.9 1.2261 209920.5\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4913 1 3196037.102001784 8.4156\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4913 1 3195955.342425258 4.7689\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4913 1 447181.8883189438 2.9456\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4913 1 362350.53850204847 2.0339\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4913 1 360383.4398402768 1.5781\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4913 1 211936.8400148848 1.3502\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4913 1 313917.73141123966 1.4641\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4913 1 220642.1923958602 1.4071\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4913 1 263678.469437509 1.4356\n",
      "I am working on tract number 4920 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4925 2.0 2 90.0 0.9783 165856.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4925 3.0 2 90.0 1.0818 165856.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4925 6.0 0 112.7 0.9205 192961.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4925 7.0 0 112.7 0.9102 192961.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4925 8.0 0 112.7 0.9 192961.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4925 9.0 0 112.7 0.8899 192961.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4925 10.0 0 112.7 0.8799 192961.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4925 11.0 0 112.7 0.87 192961.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4925 12.0 0 112.7 0.8603 192961.3\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4926 1 68238.27245432069 0.5558\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4926 1 599997.5384646822 2.258\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4926 1 335073.7073752025 1.4069\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4926 1 245027.28561719932 0.9813\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4926 1 74949.01930678476 0.7685\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4926 1 106180.16318098344 0.8749\n",
      "loop31.0, tr4926,wedgePops727373.12, 142140.5, 173496.9, 205981.8, 205753.9, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0910 \n",
      "   targetWP, latest drx4 are tWP,dr, 206069.9,0.9104, 206069.9,0.0532, 206069.9,0.027, 206069.9,0.0024\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4926 1 173496.88591923408 0.9281\n",
      "loop32.0, tr4926,wedgePops753347.62, 142140.5, 199471.4, 205981.8, 205753.9, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0910 \n",
      "   targetWP, latest drx4 are tWP,dr, 206069.9,0.9104, 206069.9,0.0266, 206069.9,0.027, 206069.9,0.0024\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4926 1 199471.3849215142 0.9547\n",
      "loop33.0, tr4926,wedgePops775979.83, 142140.5, 222103.6, 205981.8, 205753.9, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0910 \n",
      "   targetWP, latest drx4 are tWP,dr, 206069.9,0.9104, 206069.9,0.0133, 206069.9,0.027, 206069.9,0.0024\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4926 1 222103.59653187267 0.968\n",
      "loop34.0, tr4926,wedgePops764503.7, 142140.5, 210627.5, 205981.8, 205753.9, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01010 \n",
      "   targetWP, latest drx4 are tWP,dr, 206069.9,0.9104, 206069.9,-0.0066, 206069.9,0.027, 206069.9,0.0024\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4926 1 210627.46883939294 0.9614\n",
      "loop35.0, tr4926,wedgePops758812.97, 142140.5, 204936.7, 205981.8, 205753.9, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01010 \n",
      "   targetWP, latest drx4 are tWP,dr, 206069.9,0.9104, 206069.9,-0.0033, 206069.9,0.027, 206069.9,0.0024\n",
      "I am working on tract number 4940 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4947 13.0 1 61.2 1.1274 255658.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4947 19.0 1 61.2 1.2286 255658.4\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4947 1 59455.12537281774 0.5261\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4947 1 351444.9655945355 2.1876\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4947 1 255658.43042597623 1.3569\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4947 1 221730.09945410924 0.9415\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4947 1 68855.38951269028 0.7338\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4947 1 86552.48177919877 0.8376\n",
      "loop31.0, tr4947,wedgePops713228.21, 136915.1, 161176.1, 207667.3, 207469.8, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0930 \n",
      "   targetWP, latest drx4 are tWP,dr, 207811.8,0.9104, 207811.8,0.0519, 207811.8,0.0003, 207811.8,0.0033\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4947 1 161176.05195124826 0.8896\n",
      "loop32.0, tr4947,wedgePops732966.94, 136915.1, 180914.8, 207667.3, 207469.8, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0930 \n",
      "   targetWP, latest drx4 are tWP,dr, 207811.8,0.9104, 207811.8,0.026, 207811.8,0.0003, 207811.8,0.0033\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4947 1 180914.78627870796 0.9155\n",
      "loop33.0, tr4947,wedgePops750662.23, 136915.1, 198610.1, 207667.3, 207469.8, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0930 \n",
      "   targetWP, latest drx4 are tWP,dr, 207811.8,0.9104, 207811.8,0.013, 207811.8,0.0003, 207811.8,0.0033\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4947 1 198610.0756106173 0.9285\n",
      "loop34.0, tr4947,wedgePops761571.8, 136915.1, 209519.6, 207667.3, 207469.8, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0930 \n",
      "   targetWP, latest drx4 are tWP,dr, 207811.8,0.9104, 207811.8,0.0065, 207811.8,0.0003, 207811.8,0.0033\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4948 1 74917.72470859264 0.5665\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4948 1 914452.1572593794 2.3329\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4948 1 351050.52020828286 1.4497\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4948 1 243458.71431323653 1.0081\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4948 1 82784.25475524901 0.7873\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4948 1 109869.82944767483 0.8977\n",
      "loop31.0, tr4948,wedgePops733399.88, 146825.4, 177362.1, 204845.6, 204366.8, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0922 \n",
      "   targetWP, latest drx4 are tWP,dr, 204508.3,0.9104, 204508.3,0.0552, 204508.3,-0.0011, 204508.3,0.0142\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4948 1 177362.08309201768 0.9529\n",
      "loop32.0, tr4948,wedgePops755514.33, 146825.4, 199476.5, 204845.6, 204366.8, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0922 \n",
      "   targetWP, latest drx4 are tWP,dr, 204508.3,0.9104, 204508.3,0.0276, 204508.3,-0.0011, 204508.3,0.0142\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4948 1 199476.53311657993 0.9805\n",
      "loop33.0, tr4948,wedgePops775962.85, 146825.4, 219925.1, 204845.6, 204366.8, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0922 \n",
      "   targetWP, latest drx4 are tWP,dr, 204508.3,0.9104, 204508.3,0.0138, 204508.3,-0.0011, 204508.3,0.0142\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4948 1 219925.05486857315 0.9943\n",
      "loop34.0, tr4948,wedgePops764477.77, 146825.4, 208440.0, 204845.6, 204366.8, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01022 \n",
      "   targetWP, latest drx4 are tWP,dr, 204508.3,0.9104, 204508.3,-0.0069, 204508.3,-0.0011, 204508.3,0.0142\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4948 1 208439.9696312263 0.9874\n",
      "loop35.0, tr4948,wedgePops759701.1, 146825.4, 203663.3, 204845.6, 204366.8, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01022 \n",
      "   targetWP, latest drx4 are tWP,dr, 204508.3,0.9104, 204508.3,-0.0034, 204508.3,-0.0011, 204508.3,0.0142\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4956 1 216451.89905876253 1.4532\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4956 1 28140.255264932028 0.7266\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4956 1 234295.2768692344 1.5151\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4956 1 68370.40273739211 1.1209\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4956 1 114842.23009651246 1.318\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4956 1 194806.69749617684 1.4166\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4956 1 221908.13623064032 1.4658\n",
      "I am working on tract number 4960 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4979 13.0 0 105.9 1.1567 184756.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4979 14.0 0 105.9 1.1816 184756.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4979 15.0 0 105.9 1.207 184756.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4979 16.0 0 105.9 1.2329 184756.2\n",
      "I am working on tract number 4980 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4988 9.0 1 57.1 0.467 260709.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4988 10.0 1 57.1 0.4388 260709.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4988 11.0 1 57.1 0.4123 260709.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4988 12.0 1 57.1 0.3874 260709.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4988 13.0 1 57.1 0.364 260709.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 4988 14.0 1 57.1 0.342 260709.1\n",
      "7 yoyos for tract,wedge,wedgePop,r= 4999 1 216891.5834090613 2.5887\n",
      "8 yoyos for tract,wedge,wedgePop,r= 4999 1 140455.24457311365 1.2944\n",
      "9 yoyos for tract,wedge,wedgePop,r= 4999 1 216842.92432396841 2.577\n",
      "10 yoyos for tract,wedge,wedgePop,r= 4999 1 174139.4632142269 1.9357\n",
      "11 yoyos for tract,wedge,wedgePop,r= 4999 1 210128.62667293882 2.2563\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4999 1 177620.41258421727 2.096\n",
      "12 yoyos for tract,wedge,wedgePop,r= 4999 1 181447.214699758 2.1762\n",
      "13 yoyos for tract,wedge,wedgePop,r= 4999 1 195921.66552366814 2.2163\n",
      "I am working on tract number 5000 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5008 1 383513.10733821493 1.3375\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5008 1 125768.64360447339 0.6687\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5008 1 382039.03544338554 1.3288\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5008 1 184863.2454573645 0.9988\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5008 1 322673.26733274217 1.1638\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5008 1 291211.3524772801 1.0813\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5008 1 253789.57059224855 1.04\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5008 1 218246.29547090904 1.0194\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5008 1 200080.15397496248 1.0091\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5015 4.0 0 138.7 0.3065 36351.2\n",
      "I am working on tract number 5020 of 9129 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 5025\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5035 6.0 0 90.0 0.3692 177035.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5035 7.0 0 90.0 0.3892 177035.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5035 8.0 0 90.0 0.4104 177035.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5037 2.0 3 90.0 0.1951 30162.6\n",
      "I am working on tract number 5040 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5043 8.0 0 137.6 0.9669 37308.2\n",
      "I am working on tract number 5060 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5073 2.0 3 90.0 0.134 26388.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5076 7.0 3 63.9 0.3375 119466.1\n",
      "I am working on tract number 5080 of 9129 tracts\n",
      "I am working on tract number 5100 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5100 2 245616.52054236602 0.5363\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5100 2 147116.14269676656 0.2681\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5100 2 245726.62698369587 0.5369\n",
      "I am working on tract number 5120 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5123 8.0 1 36.6 1.5068 263765.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5123 9.0 1 36.6 1.4581 263765.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5123 10.0 1 36.6 1.4111 263765.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5123 15.0 1 36.6 1.4737 263765.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5123 16.0 1 36.6 1.4262 263765.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5123 17.0 1 36.6 1.3801 263765.6\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5123 1 257736.23683618067 1.3581\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5123 1 134980.06106828223 0.6791\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5123 1 263765.6251250747 1.4419\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5124 1 259551.0767789611 0.9189\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5124 1 36250.07527414613 0.4594\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5124 1 302579.3002082312 0.9607\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5124 1 143246.81740405815 0.7101\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5124 1 177748.12723654835 0.8354\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5124 1 208463.25880889856 0.898\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5124 1 275101.61376086815 0.9294\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5124 1 247459.8812860721 0.9137\n",
      "13 yoyos for tract,wedge,wedgePop,r= 5124 1 264461.2571083436 0.9215\n",
      "13 yoyos for tract,wedge,wedgePop,r= 5124 1 256850.86472093122 0.9176\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5125 2 252815.48070941714 0.8543\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5125 2 112700.77089439204 0.4271\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5125 2 256542.71066228003 0.8673\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5125 2 146927.19613013556 0.6472\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5125 2 242126.80040014355 0.7573\n",
      "I am working on tract number 5140 of 9129 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 5153\n",
      "we have 2 non-opposing shorted wedges for tract no 5155\n",
      "I am working on tract number 5160 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5173 7.0 0 140.0 0.8328 165340.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5173 8.0 0 140.0 0.923 165340.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5173 9.0 0 140.0 1.023 165340.2\n",
      "I am working on tract number 5180 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5181 7.0 2 90.0 0.5365 182935.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5181 8.0 2 90.0 0.552 182935.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5181 9.0 2 90.0 0.5681 182935.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5181 10.0 2 90.0 0.5846 182935.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5181 11.0 2 90.0 0.6015 182935.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5181 12.0 2 90.0 0.619 182935.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5181 13.0 2 90.0 0.637 182935.7\n",
      "I am working on tract number 5200 of 9129 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 5205\n",
      "I am working on tract number 5220 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5238 7.0 0 90.0 1.029 302474.6\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5238 0 360436.3091365043 1.7578\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5238 0 179601.69932086373 0.8789\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5238 0 360769.4471687552 1.8268\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5238 0 302474.55970675504 1.3528\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5238 22.0 0 90.0 1.1159 302474.6\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5238 0 302474.55970675504 1.1159\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5238 23.0 0 90.0 0.9974 302474.6\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5238 0 302474.55970675504 0.9974\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5238 0 289100.4720294512 0.9382\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5238 0 244993.65920525067 0.9085\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5238 0 210112.97404231742 0.8937\n",
      "I am working on tract number 5240 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5241 3.0 3 90.0 0.4928 71523.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5241 8.0 3 90.0 0.7902 71523.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5258 2.0 3 90.0 0.1837 52806.6\n",
      "I am working on tract number 5260 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5261 4.0 0 136.5 0.1911 44506.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5262 2.0 1 90.0 0.2832 13265.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5262 3.0 1 90.0 1.1936 13265.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5262 6.0 0 138.5 0.2212 35380.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5264 4.0 0 140.2 0.2567 23991.8\n",
      "I am working on tract number 5280 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5293 5.0 2 452.4 0.2183 12271.5\n",
      "I am working on tract number 5300 of 9129 tracts\n",
      "I am working on tract number 5320 of 9129 tracts\n",
      "I am working on tract number 5340 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5357 2.0 1 90.0 0.2351 77713.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5357 5.0 3 -272.4 0.2145 96430.2\n",
      "I am working on tract number 5360 of 9129 tracts\n",
      "I am working on tract number 5380 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5389 2.0 0 90.0 0.3218 25500.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5390 4.0 3 90.0 0.4591 100845.1\n",
      "I am working on tract number 5400 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5400 12.0 0 127.2 0.4664 151010.1\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5406 3 358268.0103927635 1.5141\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5406 3 158595.44694045218 0.7571\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5406 3 341303.44415363204 1.2871\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5406 3 226730.12735917763 1.0221\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5406 3 161812.31316103195 0.8896\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5406 3 164272.0767081979 0.9558\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5406 3 178913.58365289948 0.989\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5406 3 201552.9199419418 1.0055\n",
      "loop31.0, tr5406,wedgePops759790.8, 190377.7, 190523.7, 190045.0, 188844.5, Overedge?0, 0, 0, 0, ,Satisfied?1110,yoyo?02311 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.2093, 190087.6,0.0125, 190087.6,-0.0082, 190087.6,-0.0083\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5408 5.0 3 90.0 1.1851 138767.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5409 6.0 2 90.0 0.2394 181402.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5409 7.0 2 90.0 0.2479 181402.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5409 10.0 2 90.0 0.5835 290649.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5411 7.0 0 117.0 0.4825 107577.2\n",
      "I am working on tract number 5420 of 9129 tracts\n",
      "I am working on tract number 5440 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5443 4.0 0 141.2 0.4139 13589.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5443 6.0 0 141.2 1.7879 94476.8\n",
      "I am working on tract number 5460 of 9129 tracts\n",
      "I am working on tract number 5480 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5488 2.0 0 90.0 0.2717 7408.1\n",
      "I am working on tract number 5500 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5506 0 2729591.4872039477 2.5351\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5506 0 983663.151556741 1.2675\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5506 0 75941.04244422831 0.6338\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5506 0 1299299.8665337353 1.3242\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5506 0 82432.11603489611 0.979\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5506 0 241156.72165902617 1.1516\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5506 0 84762.191585269 1.0653\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5506 0 102126.79693177265 1.1084\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5506 0 139281.99478463782 1.13\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5510 0 295819.2848497909 1.2775\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5510 0 108001.04481976817 0.6387\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5510 0 295740.0963175604 1.2771\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5510 0 157450.47766137918 0.9579\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5510 0 258363.83943515108 1.1175\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5510 0 233578.14719297012 1.0377\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5510 0 184349.90900758625 0.9978\n",
      "13 yoyos for tract,wedge,wedgePop,r= 5510 0 210026.7553190932 1.0178\n",
      "13 yoyos for tract,wedge,wedgePop,r= 5510 0 197237.73341166845 1.0078\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5518 1 3067948.8753642906 2.539\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5518 1 1032117.2412976935 1.2695\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5518 1 82132.01037536713 0.6347\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5518 1 1296883.4843302271 1.3223\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5518 1 88614.35429264233 0.9785\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5518 1 217684.18992838287 1.1504\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5518 1 90841.73660183136 1.0645\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5518 1 104891.88864895447 1.1075\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5518 1 125794.17471295776 1.1289\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5518 1 153215.49733288103 1.1397\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5518 1 181514.0859556509 1.1451\n",
      "13 yoyos for tract,wedge,wedgePop,r= 5518 1 199506.96561970646 1.1477\n",
      "I am working on tract number 5520 of 9129 tracts\n",
      "I am working on tract number 5540 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5545 3 241352.34163260163 0.6641\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5545 3 56946.31432861442 0.332\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5545 3 242615.0696612999 0.6918\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5545 3 94130.0678025021 0.5119\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5545 3 203367.0265542737 0.6018\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5545 3 139600.1995282299 0.5569\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5545 3 167549.82177960806 0.5793\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5545 3 184157.57055347177 0.5906\n",
      "I am working on tract number 5560 of 9129 tracts\n",
      "I am working on tract number 5580 of 9129 tracts\n",
      "I am working on tract number 5600 of 9129 tracts\n",
      "I am working on tract number 5620 of 9129 tracts\n",
      "I am working on tract number 5640 of 9129 tracts\n",
      "I am working on tract number 5660 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5664 0 422324.79140423355 1.9138\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5664 0 80198.84589503187 0.9569\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5664 0 421405.6170033139 1.9096\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5664 0 119517.70206334477 1.4332\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5664 0 213796.97071144046 1.6714\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5664 0 126238.63671926015 1.5523\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5664 0 135186.10057915887 1.6119\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5664 0 145713.60739693782 1.6416\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5664 0 174623.2027344586 1.6565\n",
      "I am working on tract number 5680 of 9129 tracts\n",
      "I am working on tract number 5700 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5715 3 277631.4130321486 2.3632\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5715 3 2154.607862301171 1.1816\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5715 3 589753.8101887988 2.6764\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5715 3 50338.67776617315 1.929\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5715 3 179067.08395614033 2.3027\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5715 3 519458.79453375994 2.4895\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5715 3 329543.8289949038 2.3961\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5715 3 257772.48769977974 2.3494\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5715 3 213645.39807871173 2.326\n",
      "loop31.0, tr5715,wedgePops739813.14, 252975.4, 1007.4, 252860.9, 232969.5, Overedge?0, 1, 0, 0, ,Satisfied?1010,yoyo?00012 \n",
      "   targetWP, latest drx4 are tWP,dr, 253114.3,0.0036, 253114.3,0.9104, 253114.3,0.0078, 253114.3,0.0117\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5715 3 232969.49683816129 2.3377\n",
      "loop32.0, tr5715,wedgePops752236.2, 252975.4, 1007.4, 252860.9, 245392.6, Overedge?0, 1, 0, 0, ,Satisfied?1010,yoyo?00012 \n",
      "   targetWP, latest drx4 are tWP,dr, 253114.3,0.0036, 253114.3,0.9104, 253114.3,0.0078, 253114.3,0.0058\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5715 3 245392.55529323046 2.3435\n",
      "loop33.0, tr5715,wedgePops759204.4, 252975.4, 1007.4, 252860.9, 252360.8, Overedge?0, 1, 0, 0, ,Satisfied?1010,yoyo?00012 \n",
      "   targetWP, latest drx4 are tWP,dr, 253114.3,0.0036, 253114.3,0.9104, 253114.3,0.0078, 253114.3,0.0029\n",
      "I am working on tract number 5720 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5733 4.0 0 135.2 0.2974 74873.0\n",
      "I am working on tract number 5740 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5750 2.0 3 90.0 0.2068 46308.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5750 5.0 0 95.3 0.1982 51183.0\n",
      "I am working on tract number 5760 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5766 2 197421.01608389572 0.5966\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5766 2 105623.69029271588 0.2983\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5766 2 605163.1954726626 0.7636\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5766 2 117734.03532168688 0.531\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5766 2 319650.83385808126 0.6473\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5766 2 177334.62417945007 0.5891\n",
      "13 yoyos for tract,wedge,wedgePop,r= 5766 2 270784.83889668237 0.6182\n",
      "13 yoyos for tract,wedge,wedgePop,r= 5766 2 221843.87866684207 0.6037\n",
      "13 yoyos for tract,wedge,wedgePop,r= 5766 2 196712.9067684758 0.5964\n",
      "14 yoyos for tract,wedge,wedgePop,r= 5766 2 186525.85809501333 0.5928\n",
      "I am working on tract number 5780 of 9129 tracts\n",
      "I am working on tract number 5800 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5814 7.0 0 90.0 0.8135 300139.7\n",
      "I am working on tract number 5820 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5835 3 415693.46742013015 1.7049\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5835 3 10776.76420579513 0.8525\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5835 3 480109.73868981283 1.7601\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5835 3 74241.60563189711 1.3063\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5835 3 99998.9917026749 1.5332\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5835 3 307789.19086394284 1.6467\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5835 3 128674.43882557144 1.5899\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5835 3 222033.1108267053 1.6183\n",
      "13 yoyos for tract,wedge,wedgePop,r= 5835 3 268842.2667925228 1.6325\n",
      "13 yoyos for tract,wedge,wedgePop,r= 5835 3 244581.3242986054 1.6254\n",
      "14 yoyos for tract,wedge,wedgePop,r= 5835 3 232998.03939027974 1.6219\n",
      "I am working on tract number 5840 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5846 5.0 0 90.0 0.2892 159430.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5846 11.0 2 452.4 0.2439 165859.3\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5851 0 873149.628985721 0.8033\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5851 0 93118.27170078759 0.4017\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5851 0 870285.9189511479 0.7922\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5851 0 726290.0238994313 0.5969\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5851 0 409639.44024912745 0.4993\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5851 0 240895.0305419175 0.4505\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5851 0 156238.9754063774 0.4261\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5851 0 202360.0439707601 0.4383\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5851 0 179331.14916763824 0.4322\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5854 1 232594.6226562028 1.0446\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5854 1 166432.01502090806 0.5223\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5854 1 232646.56928870463 1.0458\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5854 1 210402.74914442655 0.7841\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5854 1 171253.469341731 0.6532\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5854 1 174175.5637163421 0.7186\n",
      "I am working on tract number 5860 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5861 1 199993.88349215692 1.0637\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5861 1 129719.36832030083 0.5319\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5861 1 230967.67251935846 1.1266\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5861 1 169454.8059215275 0.8292\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5861 1 174521.34736743398 0.9779\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5865 2.0 1 90.0 0.2147 33883.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5865 5.0 0 98.7 0.2055 37817.3\n",
      "I am working on tract number 5880 of 9129 tracts\n",
      "I am working on tract number 5900 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5905 3 271746.24893488 0.7954\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5905 3 13049.331725959259 0.3977\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5905 3 276582.13657989644 0.8344\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5905 3 70087.30468279042 0.6161\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5905 3 254067.44210930998 0.7252\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5905 3 175632.16060668998 0.6706\n",
      "13 yoyos for tract,wedge,wedgePop,r= 5905 3 227984.58671003568 0.6979\n",
      "13 yoyos for tract,wedge,wedgePop,r= 5905 3 201971.92254277974 0.6843\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5913 2 211342.2962354992 0.7518\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5913 2 134718.5641711581 0.3759\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5913 2 210425.51364734126 0.7442\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5913 2 154561.63834460385 0.5601\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5913 2 204767.58345067344 0.6522\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5913 2 166199.58407787365 0.6061\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5913 2 182719.28811235382 0.6291\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5918 0 202374.58415948978 1.1045\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5918 0 84914.97082380822 0.5522\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5918 0 395222.1352897042 1.189\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5918 0 106172.68852074392 0.8706\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5918 0 122912.58467854085 1.0298\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5918 0 214048.28667725454 1.1094\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5918 0 154644.42766974634 1.0696\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5918 0 176433.1176343223 1.0895\n",
      "I am working on tract number 5920 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5929 1 2821823.034118645 3.7765\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5929 1 2813178.9362494405 2.0493\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5929 1 1133985.4869160152 1.1858\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5929 1 41835.11974215368 0.754\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5929 1 47528.311851710285 0.9699\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5929 1 427574.01310370746 1.0778\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5929 1 112519.9888951563 1.0238\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5929 1 269340.6848318619 1.0508\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5933 9.0 1 37.6 1.2263 248210.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5933 10.0 1 37.6 1.2175 248210.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5933 11.0 1 37.6 1.2087 248210.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5933 12.0 1 37.6 1.2 248210.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5933 13.0 1 37.6 1.1914 248210.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5933 14.0 1 37.6 1.1828 248210.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5933 15.0 1 37.6 1.1743 248210.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5933 16.0 1 37.6 1.1659 248210.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5933 17.0 1 37.6 1.1575 248210.1\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5933 3 346262.88282532274 1.9929\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5933 18.0 1 37.6 1.1492 248210.1\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5933 3 111880.85255163888 0.9964\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5933 19.0 1 37.6 1.1409 248210.1\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5933 3 520896.8851321337 2.0542\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5933 20.0 1 37.6 1.1327 248210.1\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5933 3 149915.38644566003 1.5253\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5933 21.0 1 37.6 1.1246 248210.1\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5933 3 188729.06664892388 1.7898\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5933 22.0 1 37.6 1.1165 248210.1\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5933 3 210723.66867785162 1.922\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5933 23.0 1 37.6 1.1085 248210.1\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5933 3 328567.1959337465 1.9881\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5933 24.0 1 37.6 1.1005 248210.1\n",
      "12 yoyos for tract,wedge,wedgePop,r= 5933 3 225481.51153857447 1.955\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5933 25.0 1 37.6 1.0926 248210.1\n",
      "13 yoyos for tract,wedge,wedgePop,r= 5933 3 271871.0884240093 1.9716\n",
      "I am working on tract number 5940 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5946 4.0 2 90.0 0.3046 132131.2\n",
      "I am working on tract number 5960 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 5977 2 437321.8921725586 0.6599\n",
      "8 yoyos for tract,wedge,wedgePop,r= 5977 2 98298.47524353268 0.3299\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5977 2 449642.5958562863 0.6784\n",
      "9 yoyos for tract,wedge,wedgePop,r= 5977 2 379782.9263325964 0.5042\n",
      "10 yoyos for tract,wedge,wedgePop,r= 5977 2 167071.18643960002 0.417\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5977 2 284644.84728343424 0.4606\n",
      "11 yoyos for tract,wedge,wedgePop,r= 5977 2 216091.257619627 0.4388\n",
      "I am working on tract number 5980 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5981 4.0 0 90.0 0.2958 132051.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5981 5.0 0 90.0 0.3845 132051.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5981 6.0 0 90.0 0.4997 132051.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5981 7.0 0 90.0 0.6495 132051.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 5984 4.0 0 118.8 0.4631 24585.5\n",
      "I am working on tract number 6000 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6002 3 575232.7923392915 1.2432\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6002 3 133718.83912067564 0.6216\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6002 3 573511.2211545119 1.2273\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6002 3 535438.7040803526 0.9244\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6002 3 360886.38733891246 0.773\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6002 3 288235.9248812729 0.6973\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6002 3 208683.45908907958 0.6595\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6002 3 159670.51471331832 0.6405\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6002 3 180222.0688760995 0.65\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6002 3 194035.04128620928 0.6547\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6012 4.0 1 90.0 0.7279 306571.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6012 12.0 1 90.0 0.8034 306571.1\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6012 1 247195.0380004108 0.6488\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6012 1 56176.909794367064 0.3244\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6012 1 306571.1070138798 0.8093\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6012 1 100010.93121153125 0.5668\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6012 1 300690.08333859226 0.6881\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6012 1 196138.80533751432 0.6274\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6012 1 130640.4275403048 0.5971\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6012 1 162878.41939999693 0.6123\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6012 1 178980.02245996086 0.6199\n",
      "I am working on tract number 6020 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6020 5.0 2 452.4 0.1976 78986.5\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6023 1 2293838.9784150473 3.0056\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6023 1 1936571.7777431423 1.6498\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6023 1 1270992.9732526133 0.972\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6023 1 24452.093449750682 0.633\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6023 1 731795.5955908505 0.8025\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6023 1 295890.33938741975 0.7178\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6023 1 119385.50367429794 0.6754\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6023 1 207062.51578991054 0.6966\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6023 1 162032.47431131665 0.686\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6023 1 185395.59210498616 0.6913\n",
      "13 yoyos for tract,wedge,wedgePop,r= 6023 1 196475.34036765833 0.6939\n",
      "I am working on tract number 6040 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6054 1 575599.6945381251 1.0406\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6054 1 123846.97623082582 0.5203\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6054 1 576427.4145573715 1.0436\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6054 1 497953.26732768863 0.782\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6054 1 324639.63108069607 0.6511\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6058 4.0 2 452.4 0.3056 16786.8\n",
      "I am working on tract number 6060 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6060 4.0 2 277.9 0.3231 18759.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6068 2.0 3 90.0 0.3075 10491.6\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6074 0 382403.50642698933 2.3915\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6074 0 47606.98729338881 1.1957\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6074 0 346657.9180464978 1.9438\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6074 0 336380.93088487355 1.5698\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6074 0 268988.2223734841 1.3828\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6074 0 96220.2559144324 1.2893\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6074 0 172995.19628229324 1.336\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6074 0 220262.09341738027 1.3594\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6074 0 244610.38514435934 1.3711\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6074 0 257244.08678536533 1.3769\n",
      "I am working on tract number 6080 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6096 1 199585.79792936883 1.7213\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6096 1 156000.93108843095 0.8607\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6096 1 207197.52319473657 1.7804\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6096 1 168283.31222345796 1.3206\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6096 1 172522.9592060976 1.5505\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6096 1 178316.01615652887 1.6655\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6096 1 200388.6711794488 1.723\n",
      "I am working on tract number 6100 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6106 3.0 3 90.0 0.2746 102453.3\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6114 0 242575.528214489 2.5856\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6114 0 144122.77942816578 1.2928\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6114 0 292648.9565067275 3.2909\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6114 0 161825.41140905078 2.2918\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6114 0 283677.3342334494 2.7913\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6114 0 222185.49445095396 2.5416\n",
      "13 yoyos for tract,wedge,wedgePop,r= 6114 0 269774.41556231445 2.6665\n",
      "13 yoyos for tract,wedge,wedgePop,r= 6114 0 248796.04585325162 2.604\n",
      "I am working on tract number 6120 of 9129 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 6124\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6138 0 586891.2602189735 1.2903\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6138 0 171995.90608466428 0.6452\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6138 0 585580.0908688784 1.2563\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6138 0 547838.5546905225 0.9507\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6138 0 402902.65759804705 0.7979\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6138 0 319604.9402583622 0.7216\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6138 0 276575.344134839 0.6834\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6138 0 220595.76046801286 0.6643\n",
      "I am working on tract number 6140 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6143 0 466424.8665778183 0.9808\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6143 0 42349.498167243786 0.4904\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6143 0 465211.0900058945 0.9451\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6143 0 417694.0228343713 0.7177\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6143 0 239778.79615543652 0.6041\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6143 0 134605.12030422335 0.5472\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6143 0 215155.10339571483 0.5756\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6143 0 182673.87057776406 0.5614\n",
      "13 yoyos for tract,wedge,wedgePop,r= 6143 0 202087.57064035974 0.5685\n",
      "I am working on tract number 6160 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6162 4.0 3 41.3 0.2093 159267.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6165 4.0 3 39.0 0.1924 82438.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6169 2.0 2 90.0 0.3243 310332.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6172 8.0 2 452.4 0.2158 144535.2\n",
      "I am working on tract number 6180 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6192 2.0 2 90.0 0.4678 1238618.1\n",
      "I am working on tract number 6200 of 9129 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 6202\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6203 1 36359.92070464467 1.4315\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6203 1 238211.20742502366 4.4631\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6203 1 238199.81777480274 2.9473\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6203 1 93401.52601206451 2.1894\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6203 1 157001.1620801681 2.5684\n",
      "loop31.0, tr6203,wedgePops801625.77, 183730.0, 234208.1, 191853.0, 191834.7, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0921 \n",
      "   targetWP, latest drx4 are tWP,dr, 192206.8,0.2598, 192206.8,0.1895, 192206.8,-0.0118, 192206.8,0.0157\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6203 1 234208.09405991388 2.7579\n",
      "loop32.0, tr6203,wedgePops783577.58, 183730.0, 216159.9, 191853.0, 191834.7, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01021 \n",
      "   targetWP, latest drx4 are tWP,dr, 192206.8,0.2598, 192206.8,-0.0947, 192206.8,-0.0118, 192206.8,0.0157\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6203 1 216159.90908446393 2.6631\n",
      "loop33.0, tr6203,wedgePops755262.13, 183730.0, 187844.5, 191853.0, 191834.7, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01021 \n",
      "   targetWP, latest drx4 are tWP,dr, 192206.8,0.2598, 192206.8,-0.0474, 192206.8,-0.0118, 192206.8,0.0157\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6203 1 187844.4579901644 2.6157\n",
      "loop34.0, tr6203,wedgePops771267.29, 183730.0, 203849.6, 191853.0, 191834.7, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01121 \n",
      "   targetWP, latest drx4 are tWP,dr, 192206.8,0.2598, 192206.8,0.0237, 192206.8,-0.0118, 192206.8,0.0157\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6203 1 203849.61957756564 2.6394\n",
      "loop35.0, tr6203,wedgePops763732.29, 183730.0, 196314.6, 191853.0, 191834.7, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01221 \n",
      "   targetWP, latest drx4 are tWP,dr, 192206.8,0.2598, 192206.8,-0.0118, 192206.8,-0.0118, 192206.8,0.0157\n",
      "I am working on tract number 6220 of 9129 tracts\n",
      "I am working on tract number 6240 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6245 3 799594.8028054751 2.0559\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6245 3 37254.89648357511 1.0279\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6245 3 742528.0041854479 1.9864\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6245 3 107608.87620353745 1.5072\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6245 3 522898.7323550043 1.7468\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6245 3 153768.83705562726 1.627\n",
      "13 yoyos for tract,wedge,wedgePop,r= 6245 3 411792.22931630665 1.6869\n",
      "13 yoyos for tract,wedge,wedgePop,r= 6245 3 282144.5448456621 1.6569\n",
      "14 yoyos for tract,wedge,wedgePop,r= 6245 3 218465.6129962158 1.642\n",
      "15 yoyos for tract,wedge,wedgePop,r= 6245 3 247897.69251232082 1.6495\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6256 15.0 0 83.6 0.4933 185087.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6256 16.0 0 83.6 0.5033 185087.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6256 17.0 0 83.6 0.5134 185087.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6256 18.0 0 83.6 0.5237 185087.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6256 19.0 0 83.6 0.5343 185087.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6256 20.0 0 83.6 0.545 185087.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6256 21.0 0 83.6 0.556 185087.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6256 22.0 0 83.6 0.5672 185087.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6256 23.0 0 83.6 0.5786 185087.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6256 24.0 0 83.6 0.5902 185087.9\n",
      "I am working on tract number 6260 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6275 2.0 1 90.0 0.2635 9518.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6277 2.0 3 90.0 0.2084 25687.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6278 2.0 2 90.0 0.2467 14669.7\n",
      "I am working on tract number 6280 of 9129 tracts\n",
      "I am working on tract number 6300 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6306 3.0 3 -272.4 0.3867 314007.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6309 2.0 3 90.0 0.2543 66945.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6309 5.0 0 93.4 0.2586 64574.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6314 2.0 1 90.0 0.4318 3249.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6315 2.0 0 90.0 0.343 30391.4\n",
      "I am working on tract number 6320 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6331 1 507681.48441734735 0.894\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6331 1 97029.24940234126 0.447\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6331 1 507581.81243075884 0.8935\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6331 1 441983.97442483495 0.6702\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6331 1 282293.81372419867 0.5586\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6331 1 165667.1562869196 0.5028\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6331 1 252132.59508473452 0.5307\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6331 1 211843.75267259276 0.5168\n",
      "I am working on tract number 6340 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6353 3 532857.3706022765 0.914\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6353 3 86853.97996828519 0.457\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6353 3 532897.2713225307 0.9155\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6353 3 424671.7021208723 0.6863\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6353 3 234856.8322747794 0.5716\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6353 3 112864.5566458641 0.5143\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6353 3 169659.99064499434 0.543\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6353 3 204362.5079747417 0.5573\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6357 0 659973.2861321436 1.2901\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6357 0 86720.06994789257 0.645\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6357 0 660489.1759377975 1.3027\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6357 0 622516.7584507052 0.9738\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6357 0 403519.27838191635 0.8094\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6357 0 297917.33684196585 0.7272\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6357 0 198691.2089314534 0.6861\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6357 0 128966.08053868616 0.6656\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6357 0 165404.38918530883 0.6759\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6357 0 183273.78949060699 0.681\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6358 2 665009.8156959456 1.3021\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6358 2 98405.8212021112 0.6511\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6358 2 664434.4818344496 1.2883\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6358 2 626926.535879373 0.9697\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6358 2 411159.975459611 0.8104\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6358 2 315521.65708085033 0.7307\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6358 2 225227.32787568826 0.6909\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6358 2 163594.49415856914 0.671\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6358 2 196782.736643365 0.6809\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6358 2 181433.7739411963 0.6759\n",
      "I am working on tract number 6360 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6362 2 823275.4997763818 1.3003\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6362 2 309888.6125894392 0.6501\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6362 2 86558.15434215913 0.3251\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6362 2 299469.30664110975 0.6397\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6362 2 91579.4972066455 0.4824\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6362 2 114133.7365601553 0.5611\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6362 2 215289.55673905235 0.6004\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6362 2 151281.5230730782 0.5807\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6362 2 181584.94850928625 0.5906\n",
      "13 yoyos for tract,wedge,wedgePop,r= 6362 2 198143.02424543272 0.5955\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6364 5.0 1 90.0 0.4008 203632.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6364 6.0 1 90.0 0.3805 203632.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6365 3.0 1 90.0 0.4124 362616.0\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6379 1 198322.66683077393 1.886\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6379 1 142625.20282622476 0.943\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6379 1 198321.90840842476 1.8858\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6379 1 158378.20151665536 1.4144\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6379 1 195348.17000680888 1.6501\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6379 1 165100.3371768285 1.5323\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6379 1 175355.86604648214 1.5912\n",
      "I am working on tract number 6380 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6382 2 204583.40300338686 2.5387\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6382 2 123707.42832426219 1.2694\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6382 2 205850.06228657145 2.7437\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6382 2 162010.88593809342 2.0065\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6382 2 200342.34016315395 2.3751\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6382 2 166408.0113190471 2.1908\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6382 2 170441.7600973323 2.283\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6382 2 184228.1785811242 2.3291\n",
      "I am working on tract number 6400 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6402 4.0 3 90.0 0.7689 127038.4\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6417 2 295150.2960250426 1.3011\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6417 2 46492.37103117778 0.6505\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6417 2 318842.87211510167 1.6067\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6417 2 144021.52764866376 1.1286\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6417 2 300988.2912344147 1.3677\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6417 2 291121.16986530175 1.2481\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6417 2 246319.2522328624 1.1884\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6417 2 200249.3920588391 1.1585\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6417 2 167433.5022591067 1.1436\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6417 2 183137.34575297774 1.151\n",
      "I am working on tract number 6420 of 9129 tracts\n",
      "I am working on tract number 6440 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6441 3 504340.07921968465 1.2157\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6441 3 160583.70821077173 0.6078\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6441 3 496178.07956884115 1.1038\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6441 3 462308.0017100344 0.8558\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6441 3 332379.86185793136 0.7318\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6441 3 250563.1505870376 0.6698\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6441 3 226092.23744474383 0.6388\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6441 3 203701.6529311856 0.6233\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6441 3 183689.4335548021 0.6156\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6441 3 194231.19288188787 0.6195\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6445 3.0 2 90.0 0.8584 193716.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6445 4.0 2 90.0 0.8462 193716.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6445 5.0 2 90.0 0.8343 193716.5\n",
      "I am working on tract number 6460 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6471 15.0 1 81.1 2.9537 228727.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6471 20.0 1 81.1 2.9329 228727.0\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6471 1 228726.972987128 2.9514\n",
      "loop31.0, tr6471,wedgePops696336.16, 150748.0, 45887.1, 282199.3, 217501.7, Overedge?1, 1, 0, 1, ,Satisfied?0000,yoyo?0000 \n",
      "   targetWP, latest drx4 are tWP,dr, 346213.5,0.9104, 346213.5,-1.4757, 346213.5,-0.0018, 346213.5,0.9104\n",
      "loop32.0, tr6471,wedgePops719198.7, 150748.0, 45887.1, 305061.9, 217501.7, Overedge?1, 1, 0, 1, ,Satisfied?0000,yoyo?0010 \n",
      "   targetWP, latest drx4 are tWP,dr, 346213.5,0.9104, 346213.5,-1.4757, 346213.5,0.0835, 346213.5,0.9104\n",
      "loop33.0, tr6471,wedgePops742715.96, 150748.0, 45887.1, 328579.1, 217501.7, Overedge?1, 1, 0, 1, ,Satisfied?0000,yoyo?0010 \n",
      "   targetWP, latest drx4 are tWP,dr, 346213.5,0.9104, 346213.5,-1.4757, 346213.5,0.1124, 346213.5,0.9104\n",
      "loop34.0, tr6471,wedgePops756601.16, 150748.0, 45887.1, 342464.3, 217501.7, Overedge?1, 1, 0, 1, ,Satisfied?0000,yoyo?0010 \n",
      "   targetWP, latest drx4 are tWP,dr, 346213.5,0.9104, 346213.5,-1.4757, 346213.5,0.0638, 346213.5,0.9104\n",
      "I am working on tract number 6480 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6489 10.0 3 45.9 0.3987 160454.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6489 11.0 3 45.9 0.4909 160454.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6489 12.0 3 45.9 0.6044 160454.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6489 13.0 3 45.9 0.7442 160454.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6490 14.0 3 47.0 0.6079 191927.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6490 15.0 3 47.0 0.6553 191927.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6492 2.0 2 90.0 0.3302 27612.3\n",
      "I am working on tract number 6500 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6501 2.0 1 90.0 0.4518 12702.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6501 13.0 1 90.0 0.9795 12702.6\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6501 1 1661561.833494751 4.1753\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6501 1 1176162.6868302457 2.5774\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6501 1 508747.68323897384 1.7785\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6501 1 352743.0233675566 1.379\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6501 1 14308.853285259567 1.1793\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6501 1 94672.30657344568 1.2791\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6501 1 244398.53200545526 1.3291\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6502 3.0 3 37.6 0.1809 101713.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6505 6.0 3 41.2 0.7659 128905.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6507 7.0 3 44.7 0.3059 133986.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6507 8.0 3 44.7 0.3936 133986.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6508 3.0 1 90.0 0.2414 88060.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6508 12.0 0 117.1 0.3922 184467.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6508 13.0 0 117.1 0.4011 184467.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6508 14.0 0 117.1 0.4102 184467.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6508 15.0 0 117.1 0.4195 184467.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6508 16.0 0 117.1 0.429 184467.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6509 3.0 2 90.0 0.2097 93463.7\n",
      "I am working on tract number 6520 of 9129 tracts\n",
      "I am working on tract number 6540 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6544 3 291086.3382246927 1.4069\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6544 3 6137.137276934227 0.7034\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6544 3 290346.4221605141 1.3981\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6544 3 77417.37348129734 1.0508\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6550 3 125628.25553247609 1.167\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6550 3 316949.1691195072 3.9149\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6550 3 316530.50877557916 2.541\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6550 3 296505.5137682781 1.854\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6550 3 138054.49749252643 1.5105\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6550 3 222870.265897236 1.6823\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6550 3 253454.74445470978 1.7681\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6550 3 245931.66015421832 1.7252\n",
      "loop31.0, tr6550,wedgePops769863.38, 66214.9, 231241.1, 231367.5, 241039.9, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?02010 \n",
      "   targetWP, latest drx4 are tWP,dr, 231378.5,0.9104, 231378.5,0.0003, 231378.5,0.0021, 231378.5,-0.0215\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6550 3 241039.87453729438 1.7037\n",
      "loop32.0, tr6550,wedgePops763016.34, 66214.9, 231241.1, 231367.5, 234192.8, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?02010 \n",
      "   targetWP, latest drx4 are tWP,dr, 231378.5,0.9104, 231378.5,0.0003, 231378.5,0.0021, 231378.5,-0.0107\n",
      "I am working on tract number 6560 of 9129 tracts\n",
      "I am working on tract number 6580 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6591 2.0 3 90.0 0.7376 18871.8\n",
      "I am working on tract number 6600 of 9129 tracts\n",
      "I am working on tract number 6620 of 9129 tracts\n",
      "I am working on tract number 6640 of 9129 tracts\n",
      "I am working on tract number 6660 of 9129 tracts\n",
      "I am working on tract number 6680 of 9129 tracts\n",
      "I am working on tract number 6700 of 9129 tracts\n",
      "I am working on tract number 6720 of 9129 tracts\n",
      "I am working on tract number 6740 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6746 17.0 0 84.0 2.8476 209064.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6746 18.0 0 84.0 2.836 209064.7\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6747 3 120486.13244176752 1.2649\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6747 3 245623.57546767226 2.8275\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6747 3 245503.67794084176 2.0462\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6747 3 242746.07432969986 1.6556\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6747 3 202702.0867923592 1.4603\n",
      "loop31.0, tr6747,wedgePops778835.33, 97235.8, 220728.4, 220755.8, 240115.4, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?0049 \n",
      "   targetWP, latest drx4 are tWP,dr, 221038.2,0.9104, 221038.2,0.0311, 221038.2,0.001, 221038.2,0.0977\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6747 3 240115.36639375368 1.5579\n",
      "loop32.0, tr6747,wedgePops768503.9, 97235.8, 220728.4, 220755.8, 229783.9, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?00410 \n",
      "   targetWP, latest drx4 are tWP,dr, 221038.2,0.9104, 221038.2,0.0311, 221038.2,0.001, 221038.2,-0.0488\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6747 3 229783.9346066276 1.5091\n",
      "loop33.0, tr6747,wedgePops746901.68, 97235.8, 220728.4, 220755.8, 208181.7, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?00410 \n",
      "   targetWP, latest drx4 are tWP,dr, 221038.2,0.9104, 221038.2,0.0311, 221038.2,0.001, 221038.2,-0.0244\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6747 3 208181.71595768695 1.4847\n",
      "loop34.0, tr6747,wedgePops758262.37, 97235.8, 220728.4, 220755.8, 219542.4, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?00411 \n",
      "   targetWP, latest drx4 are tWP,dr, 221038.2,0.9104, 221038.2,0.0311, 221038.2,0.001, 221038.2,0.0122\n",
      "I am working on tract number 6760 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6765 0 2944079.309893366 1.8504\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6765 0 78439.2753368942 0.9252\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6765 0 3052329.3083690056 2.0783\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6765 0 2412559.819610863 1.5018\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6765 0 1059668.376096255 1.2135\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6765 0 206752.09532215993 1.0694\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6765 0 82393.85518443151 0.9973\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6765 0 103917.86466432814 1.0333\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6765 0 135549.25677929062 1.0513\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6765 0 167984.0100638807 1.0603\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6765 0 186336.35947738794 1.0648\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6765 0 196253.8692112685 1.0671\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6766 0 2429539.472978891 1.6409\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6766 0 65972.85854545655 0.8205\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6766 0 2686424.977145226 1.9732\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6766 0 2022633.5255873844 1.3968\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6766 0 1480286.4937161505 1.1086\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6766 0 420080.074695098 0.9645\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6766 0 123652.93718967336 0.8925\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6766 0 234572.96344432712 0.9285\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6766 0 166920.54101656558 0.9105\n",
      "13 yoyos for tract,wedge,wedgePop,r= 6766 0 197151.85796976602 0.9195\n",
      "14 yoyos for tract,wedge,wedgePop,r= 6766 0 181081.25611491807 0.915\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6779 8.0 1 56.9 0.8965 195142.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6779 9.0 1 56.9 0.879 195142.0\n",
      "I am working on tract number 6780 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6780 1 305550.359625511 1.1749\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6780 1 105592.81977560124 0.5875\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6780 1 293298.0038043326 1.1141\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6780 1 178342.78853865055 0.8508\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6780 1 286705.9819252349 0.9824\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6780 1 282600.2646131783 0.9166\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6780 1 255692.46769569893 0.8837\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6780 1 208379.02102912968 0.8672\n",
      "13 yoyos for tract,wedge,wedgePop,r= 6780 1 234529.4299511537 0.8754\n",
      "13 yoyos for tract,wedge,wedgePop,r= 6780 1 221576.87217244733 0.8713\n",
      "loop31.0, tr6780,wedgePops760809.74, 118754.3, 214766.3, 213545.4, 213743.8, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01300 \n",
      "   targetWP, latest drx4 are tWP,dr, 213865.4,0.9104, 213865.4,-0.0021, 213865.4,0.0017, 213865.4,0.0002\n",
      "I am working on tract number 6800 of 9129 tracts\n",
      "I am working on tract number 6820 of 9129 tracts\n",
      "I am working on tract number 6840 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6847 0 217599.98269141107 2.2934\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6847 0 43458.24029667891 1.1467\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6847 0 218196.62464065998 2.3469\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6847 0 161034.2705728257 1.7468\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6847 0 172091.4940206585 2.0469\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6847 0 216268.7086912716 2.1969\n",
      "I am working on tract number 6860 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6878 6.0 0 89.7 0.28 191445.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6878 7.0 0 89.7 0.2785 191445.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6878 8.0 0 89.7 0.277 191445.0\n",
      "I am working on tract number 6880 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6882 7.0 0 83.4 0.276 170674.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6886 8.0 3 47.4 0.3089 172863.1\n",
      "I am working on tract number 6900 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6906 1 210468.03260760318 2.5541\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6906 1 68494.54930770816 1.277\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6906 1 212270.85658150827 2.6913\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6906 1 91676.22318598218 1.9842\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6906 1 181160.37849979856 2.3377\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6906 1 209633.04174639552 2.5145\n",
      "loop31.0, tr6906,wedgePops778298.44, 189899.2, 207784.7, 190374.5, 190240.0, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?21131 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0419, 190087.6,-0.0884, 190087.6,-0.001, 190087.6,-0.0063\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6906 1 207784.66395162363 2.4261\n",
      "loop32.0, tr6906,wedgePops774270.75, 189899.2, 203757.0, 190374.5, 190240.0, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?21131 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0419, 190087.6,-0.0442, 190087.6,-0.001, 190087.6,-0.0063\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6906 1 203756.9756706997 2.3819\n",
      "loop33.0, tr6906,wedgePops766482.56, 189899.2, 195968.8, 190374.5, 190240.0, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?21131 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0419, 190087.6,-0.0221, 190087.6,-0.001, 190087.6,-0.0063\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6906 1 195968.78629502904 2.3598\n",
      "loop34.0, tr6906,wedgePops760515.3, 189899.2, 190001.5, 190374.5, 190240.0, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?21131 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0419, 190087.6,-0.011, 190087.6,-0.001, 190087.6,-0.0063\n",
      "we have 2 non-opposing shorted wedges for tract no 6919\n",
      "I am working on tract number 6920 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6922 3.0 0 115.7 0.6691 130409.0\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6923 2 486330.06014565955 2.4722\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6923 2 26492.58311582828 1.2361\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6923 2 491536.75176530407 2.4784\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6923 2 300449.6621489333 1.8572\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6923 2 62816.77026924433 1.5467\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6923 2 149656.00939769953 1.702\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6923 2 214796.5090800435 1.7796\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6923 2 248226.79853410798 1.8184\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6923 2 229807.76356155518 1.799\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6931 10.0 3 48.7 1.2365 248529.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6931 11.0 3 48.7 1.1845 248529.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6932 2.0 0 90.0 0.9228 202028.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6932 3.0 0 90.0 0.8812 202028.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6932 4.0 0 90.0 0.8416 202028.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6932 5.0 0 90.0 0.8037 202028.6\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6932 2 784775.8435134002 1.6231\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6932 0 190896.43128061737 0.5359\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6932 2 20283.83619588113 0.8115\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6932 0 571.237847385928 0.2679\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6932 2 787444.822318348 1.6587\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6932 0 200612.81371121464 0.5614\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6932 2 635313.2726772642 1.2351\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6932 0 24529.056290435896 0.4147\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6932 2 91481.6407962963 1.0233\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6932 0 146010.23589234345 0.488\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6932 2 366975.76154058357 1.1292\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6932 0 172525.42047177954 0.5247\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6932 2 245573.82115736784 1.0763\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6932 0 199408.4732366835 0.543\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6932 2 164235.02841912967 1.0498\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6932 0 187012.84926190414 0.5339\n",
      "13 yoyos for tract,wedge,wedgePop,r= 6932 2 209087.994765746 1.063\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6933 5.0 3 47.5 1.3137 191591.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6933 6.0 3 47.5 1.306 191591.0\n",
      "I am working on tract number 6940 of 9129 tracts\n",
      "need to widen edge circle beyond 0.0015163541195759884 for tract (x,y)=( -122.2744616167502 37.46539145444527\n",
      "need to widen edge circle beyond 0.0016679895315335873 for tract (x,y)=( -122.2744616167502 37.46539145444527\n",
      "need to widen edge circle beyond 0.0018347884846869461 for tract (x,y)=( -122.2744616167502 37.46539145444527\n",
      "need to widen edge circle beyond 0.002018267333155641 for tract (x,y)=( -122.2744616167502 37.46539145444527\n",
      "need to widen edge circle beyond 0.002220094066471205 for tract (x,y)=( -122.2744616167502 37.46539145444527\n",
      "need to widen edge circle beyond 0.0024421034731183255 for tract (x,y)=( -122.2744616167502 37.46539145444527\n",
      "need to widen edge circle beyond 0.0026863138204301583 for tract (x,y)=( -122.2744616167502 37.46539145444527\n",
      "need to widen edge circle beyond 0.0029549452024731746 for tract (x,y)=( -122.2744616167502 37.46539145444527\n",
      "need to widen edge circle beyond 0.0032504397227204923 for tract (x,y)=( -122.2744616167502 37.46539145444527\n",
      "need to widen edge circle beyond 0.0035754836949925418 for tract (x,y)=( -122.2744616167502 37.46539145444527\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "need to widen edge circle beyond 0.0009542237905228901 for tract (x,y)=( -122.27749254197475 37.504826825501844\n",
      "need to widen edge circle beyond 0.0010496461695751792 for tract (x,y)=( -122.27749254197475 37.504826825501844\n",
      "need to widen edge circle beyond 0.0011546107865326972 for tract (x,y)=( -122.27749254197475 37.504826825501844\n",
      "need to widen edge circle beyond 0.001270071865185967 for tract (x,y)=( -122.27749254197475 37.504826825501844\n",
      "need to widen edge circle beyond 0.0013970790517045637 for tract (x,y)=( -122.27749254197475 37.504826825501844\n",
      "need to widen edge circle beyond 0.0015367869568750202 for tract (x,y)=( -122.27749254197475 37.504826825501844\n",
      "need to widen edge circle beyond 0.0016904656525625224 for tract (x,y)=( -122.27749254197475 37.504826825501844\n",
      "need to widen edge circle beyond 0.0018595122178187747 for tract (x,y)=( -122.27749254197475 37.504826825501844\n",
      "need to widen edge circle beyond 0.0020454634396006523 for tract (x,y)=( -122.27749254197475 37.504826825501844\n",
      "need to widen edge circle beyond 0.002250009783560718 for tract (x,y)=( -122.27749254197475 37.504826825501844\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6943 8.0 0 112.3 0.2921 171524.9\n",
      "need to widen edge circle beyond 0.0006520564776608468 for tract (x,y)=( -122.25842601555127 37.5514433521398\n",
      "need to widen edge circle beyond 0.0007172621254269315 for tract (x,y)=( -122.25842601555127 37.5514433521398\n",
      "need to widen edge circle beyond 0.0007889883379696247 for tract (x,y)=( -122.25842601555127 37.5514433521398\n",
      "need to widen edge circle beyond 0.0008678871717665873 for tract (x,y)=( -122.25842601555127 37.5514433521398\n",
      "need to widen edge circle beyond 0.0009546758889432462 for tract (x,y)=( -122.25842601555127 37.5514433521398\n",
      "need to widen edge circle beyond 0.0010501434778375709 for tract (x,y)=( -122.25842601555127 37.5514433521398\n",
      "need to widen edge circle beyond 0.001155157825621328 for tract (x,y)=( -122.25842601555127 37.5514433521398\n",
      "need to widen edge circle beyond 0.001270673608183461 for tract (x,y)=( -122.25842601555127 37.5514433521398\n",
      "need to widen edge circle beyond 0.0013977409690018071 for tract (x,y)=( -122.25842601555127 37.5514433521398\n",
      "need to widen edge circle beyond 0.001537515065901988 for tract (x,y)=( -122.25842601555127 37.5514433521398\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6948 8.0 0 119.3 0.3354 182056.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6948 9.0 0 119.3 0.3464 182056.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6948 10.0 0 119.3 0.3578 182056.5\n",
      "I am working on tract number 6960 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6975 0 2450626.711993575 3.4029\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6975 0 789769.1864079807 1.7015\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6975 0 10541.411372932605 0.8507\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6975 0 603283.9719564468 1.36\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6975 0 275487.74883874063 1.1054\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6975 0 18819.642620269675 0.9781\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6975 0 82106.62421107518 1.0417\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6975 0 150899.4063185164 1.0735\n",
      "11 yoyos for tract,wedge,wedgePop,r= 6975 0 209093.4249537772 1.0895\n",
      "12 yoyos for tract,wedge,wedgePop,r= 6975 0 177370.01674673223 1.0815\n",
      "I am working on tract number 6980 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 6982 2 551454.673245214 0.7866\n",
      "8 yoyos for tract,wedge,wedgePop,r= 6982 2 20226.060619186726 0.3933\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6982 2 521728.91617803497 0.7635\n",
      "9 yoyos for tract,wedge,wedgePop,r= 6982 2 272306.9411934086 0.5784\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6982 2 36687.565975594334 0.4859\n",
      "10 yoyos for tract,wedge,wedgePop,r= 6982 2 113905.34468944752 0.5321\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6986 2.0 0 90.0 0.544 4610.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 6986 5.0 0 141.6 0.349 19406.2\n",
      "we have 2 non-opposing shorted wedges for tract no 6992\n",
      "I am working on tract number 7000 of 9129 tracts\n",
      "I am working on tract number 7020 of 9129 tracts\n",
      "I am working on tract number 7040 of 9129 tracts\n",
      "I am working on tract number 7060 of 9129 tracts\n",
      "I am working on tract number 7080 of 9129 tracts\n",
      "need to widen edge circle beyond 0.0007736871339877863 for tract (x,y)=( -122.15624524777913 37.733054439186496\n",
      "need to widen edge circle beyond 0.000851055847386565 for tract (x,y)=( -122.15624524777913 37.733054439186496\n",
      "need to widen edge circle beyond 0.0009361614321252216 for tract (x,y)=( -122.15624524777913 37.733054439186496\n",
      "need to widen edge circle beyond 0.0010297775753377438 for tract (x,y)=( -122.15624524777913 37.733054439186496\n",
      "need to widen edge circle beyond 0.0011327553328715182 for tract (x,y)=( -122.15624524777913 37.733054439186496\n",
      "need to widen edge circle beyond 0.0012460308661586701 for tract (x,y)=( -122.15624524777913 37.733054439186496\n",
      "need to widen edge circle beyond 0.0013706339527745372 for tract (x,y)=( -122.15624524777913 37.733054439186496\n",
      "need to widen edge circle beyond 0.001507697348051991 for tract (x,y)=( -122.15624524777913 37.733054439186496\n",
      "need to widen edge circle beyond 0.0016584670828571901 for tract (x,y)=( -122.15624524777913 37.733054439186496\n",
      "need to widen edge circle beyond 0.0018243137911429094 for tract (x,y)=( -122.15624524777913 37.733054439186496\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "7 yoyos for tract,wedge,wedgePop,r= 7089 3 816399.2145752617 0.8194\n",
      "7 yoyos for tract,wedge,wedgePop,r= 7089 3 720623.9026068253 0.4097\n",
      "8 yoyos for tract,wedge,wedgePop,r= 7089 3 13518.35855856957 0.2049\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7089 3 599442.2513898042 0.346\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7089 3 87648.94322970381 0.2754\n",
      "11 yoyos for tract,wedge,wedgePop,r= 7089 3 299264.223793514 0.3107\n",
      "12 yoyos for tract,wedge,wedgePop,r= 7089 3 171292.99245719402 0.2931\n",
      "13 yoyos for tract,wedge,wedgePop,r= 7089 3 226497.5087538791 0.3019\n",
      "13 yoyos for tract,wedge,wedgePop,r= 7089 3 197730.91765342464 0.2975\n",
      "14 yoyos for tract,wedge,wedgePop,r= 7089 3 184227.6927959179 0.2953\n",
      "need to widen edge circle beyond 0.0009192122586707509 for tract (x,y)=( -122.26142657572728 37.54062177479715\n",
      "need to widen edge circle beyond 0.001011133484537826 for tract (x,y)=( -122.26142657572728 37.54062177479715\n",
      "need to widen edge circle beyond 0.0011122468329916087 for tract (x,y)=( -122.26142657572728 37.54062177479715\n",
      "need to widen edge circle beyond 0.0012234715162907697 for tract (x,y)=( -122.26142657572728 37.54062177479715\n",
      "need to widen edge circle beyond 0.0013458186679198467 for tract (x,y)=( -122.26142657572728 37.54062177479715\n",
      "need to widen edge circle beyond 0.0014804005347118314 for tract (x,y)=( -122.26142657572728 37.54062177479715\n",
      "need to widen edge circle beyond 0.0016284405881830148 for tract (x,y)=( -122.26142657572728 37.54062177479715\n",
      "need to widen edge circle beyond 0.0017912846470013164 for tract (x,y)=( -122.26142657572728 37.54062177479715\n",
      "need to widen edge circle beyond 0.0019704131117014483 for tract (x,y)=( -122.26142657572728 37.54062177479715\n",
      "need to widen edge circle beyond 0.0021674544228715933 for tract (x,y)=( -122.26142657572728 37.54062177479715\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "I am working on tract number 7100 of 9129 tracts\n",
      "I am working on tract number 7120 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7127 2.0 3 90.0 0.1619 23245.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7127 8.0 0 135.5 0.8385 35138.4\n",
      "7 yoyos for tract,wedge,wedgePop,r= 7127 3 333076.06853822444 1.0681\n",
      "8 yoyos for tract,wedge,wedgePop,r= 7127 3 112653.52932632691 0.5341\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7127 3 354713.9560398549 1.2003\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7127 3 187439.1102415339 0.8672\n",
      "11 yoyos for tract,wedge,wedgePop,r= 7127 3 324587.0492785681 1.0338\n",
      "11 yoyos for tract,wedge,wedgePop,r= 7127 3 308992.4974712951 0.9505\n",
      "11 yoyos for tract,wedge,wedgePop,r= 7127 3 261440.45046248485 0.9088\n",
      "12 yoyos for tract,wedge,wedgePop,r= 7127 3 220674.07198278053 0.888\n",
      "I am working on tract number 7140 of 9129 tracts\n",
      "I am working on tract number 7160 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7161 3.0 0 90.0 0.2466 107094.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7177 6.0 2 90.0 0.6956 114053.3\n",
      "I am working on tract number 7180 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7183 4.0 0 133.8 0.2616 59888.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7183 5.0 0 133.8 0.5683 59888.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7184 3.0 0 90.0 0.2102 74862.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7184 9.0 0 115.0 1.1072 132946.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7185 2.0 0 90.0 0.3307 9702.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7186 4.0 0 90.0 0.4535 156585.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7190 4.0 0 143.5 0.4529 10699.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7191 4.0 0 135.4 0.3079 51962.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7199 2.0 2 90.0 0.23 8039.1\n",
      "I am working on tract number 7200 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7203 2.0 0 90.0 0.1868 60695.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7203 11.0 0 127.9 0.4649 152049.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7204 2.0 0 90.0 0.2271 46685.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7204 5.0 0 131.6 0.2245 66603.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7204 6.0 0 131.6 0.4566 66603.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7204 7.0 0 131.6 0.9288 66603.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7204 11.0 0 131.6 0.8526 66603.0\n",
      "7 yoyos for tract,wedge,wedgePop,r= 7219 1 211173.461415262 0.6361\n",
      "8 yoyos for tract,wedge,wedgePop,r= 7219 1 26231.191863586835 0.3181\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7219 1 221886.87155953996 0.6935\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7219 1 67149.62098350006 0.5058\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7219 1 150936.32685673898 0.5996\n",
      "11 yoyos for tract,wedge,wedgePop,r= 7219 1 216411.08132244227 0.6466\n",
      "11 yoyos for tract,wedge,wedgePop,r= 7219 1 196578.6108079221 0.6231\n",
      "12 yoyos for tract,wedge,wedgePop,r= 7219 1 175618.8969816911 0.6114\n",
      "12 yoyos for tract,wedge,wedgePop,r= 7219 1 186783.6993890936 0.6172\n",
      "I am working on tract number 7220 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7223 6.0 1 90.0 0.399 170407.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7223 15.0 0 102.7 0.3549 186372.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7223 16.0 0 102.7 0.3602 186372.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7223 17.0 0 102.7 0.3655 186372.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7223 18.0 0 102.7 0.3709 186372.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7223 19.0 0 102.7 0.3765 186372.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7223 20.0 0 102.7 0.3821 186372.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7223 21.0 0 102.7 0.3877 186372.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7223 22.0 0 102.7 0.3935 186372.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7223 23.0 0 102.7 0.3994 186372.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7223 24.0 0 102.7 0.4053 186372.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7229 2.0 0 90.0 0.2375 54945.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7229 7.0 0 85.0 0.5943 193360.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7235 6.0 0 143.2 1.267 148393.4\n",
      "I am working on tract number 7240 of 9129 tracts\n",
      "I am working on tract number 7260 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7262 4.0 3 90.0 0.859 275282.4\n",
      "7 yoyos for tract,wedge,wedgePop,r= 7268 0 249739.7318941874 0.5572\n",
      "8 yoyos for tract,wedge,wedgePop,r= 7268 0 147002.01087498595 0.2786\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7268 0 249897.4310784074 0.558\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7274 4.0 2 452.4 0.1744 16311.0\n",
      "I am working on tract number 7280 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7280 5.0 2 90.0 0.8552 222968.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7280 6.0 2 90.0 0.7568 222968.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7280 7.0 2 90.0 0.6698 222968.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7280 8.0 2 90.0 0.5927 222968.0\n",
      "I am working on tract number 7300 of 9129 tracts\n",
      "I am working on tract number 7320 of 9129 tracts\n",
      "I am working on tract number 7340 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 7342 3 207619.47207130774 0.209\n",
      "8 yoyos for tract,wedge,wedgePop,r= 7342 3 78496.53642229122 0.1045\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7342 3 1023595.850783243 0.3154\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7342 3 214373.57675994514 0.2099\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7342 3 81840.12354823717 0.1572\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7342 3 93479.16119573454 0.1836\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7342 3 138870.7791948174 0.1968\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7342 3 171910.0345505801 0.2034\n",
      "I am working on tract number 7360 of 9129 tracts\n",
      "I am working on tract number 7380 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 7392 1 522861.94042617595 0.9941\n",
      "8 yoyos for tract,wedge,wedgePop,r= 7392 1 64309.446794032934 0.4971\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7392 1 523469.404271708 0.9977\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7392 1 428353.30348967836 0.7474\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7392 1 233765.0009407877 0.6222\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7392 1 104550.94904262459 0.5597\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7392 1 163616.31755815356 0.5909\n",
      "11 yoyos for tract,wedge,wedgePop,r= 7392 1 198992.23521371855 0.6066\n",
      "12 yoyos for tract,wedge,wedgePop,r= 7392 1 181230.53713925084 0.5988\n",
      "I am working on tract number 7400 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7412 2.0 1 90.0 0.2947 490654.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7413 2.0 3 90.0 0.7424 322030.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7413 3.0 3 90.0 0.4843 322030.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7413 4.0 3 90.0 0.316 322030.5\n",
      "I am working on tract number 7420 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7421 2.0 3 90.0 0.702 375169.6\n",
      "I am working on tract number 7440 of 9129 tracts\n",
      "I am working on tract number 7460 of 9129 tracts\n",
      "I am working on tract number 7480 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7487 3.0 1 90.0 0.4653 280859.2\n",
      "I am working on tract number 7500 of 9129 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 7511\n",
      "we have 2 non-opposing shorted wedges for tract no 7512\n",
      "I am working on tract number 7520 of 9129 tracts\n",
      "I am working on tract number 7540 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7543 4.0 3 39.6 0.4141 15398.9\n",
      "I am working on tract number 7560 of 9129 tracts\n",
      "I am working on tract number 7580 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 7597 3 203994.48686565948 2.6816\n",
      "8 yoyos for tract,wedge,wedgePop,r= 7597 3 91273.23685423595 1.3408\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7597 3 236543.31331613846 3.1114\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7597 3 115304.06086646391 2.2261\n",
      "I am working on tract number 7600 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7600 5.0 0 142.4 0.9181 116486.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7611 6.0 0 133.1 0.5493 151193.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7611 7.0 0 133.1 0.6493 151193.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7611 8.0 0 133.1 0.7674 151193.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7611 13.0 0 133.1 0.7771 151193.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7611 18.0 0 133.1 0.7785 151193.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7611 21.0 0 133.1 1.3762 350958.8\n",
      "7 yoyos for tract,wedge,wedgePop,r= 7611 0 349738.0175769037 1.3335\n",
      "8 yoyos for tract,wedge,wedgePop,r= 7611 0 151193.34619833587 0.6667\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7611 0 350958.8364100209 1.6865\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7611 0 292272.140801267 1.1766\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7611 0 153434.5114494696 0.9217\n",
      "11 yoyos for tract,wedge,wedgePop,r= 7611 0 215775.17570291675 1.0491\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7612 9.0 0 102.3 0.7003 145880.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7612 10.0 0 102.3 0.8489 145880.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7613 4.0 0 112.3 0.241 121923.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7613 5.0 0 112.3 0.3309 121923.6\n",
      "7 yoyos for tract,wedge,wedgePop,r= 7617 3 280989.2472457703 4.0938\n",
      "8 yoyos for tract,wedge,wedgePop,r= 7617 3 150054.65796238458 2.0469\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7617 3 280989.2472457704 3.9797\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7617 3 170074.4809695537 3.0133\n",
      "11 yoyos for tract,wedge,wedgePop,r= 7617 3 278860.2340818483 3.4965\n",
      "12 yoyos for tract,wedge,wedgePop,r= 7617 3 191986.58023733686 3.2549\n",
      "13 yoyos for tract,wedge,wedgePop,r= 7617 3 247912.70916800573 3.3757\n",
      "14 yoyos for tract,wedge,wedgePop,r= 7617 3 198777.91325712256 3.3153\n",
      "14 yoyos for tract,wedge,wedgePop,r= 7617 3 216315.9739519731 3.3455\n",
      "14 yoyos for tract,wedge,wedgePop,r= 7617 3 231816.19272931875 3.3606\n",
      "I am working on tract number 7620 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7625 3.0 2 90.0 0.2519 96812.4\n",
      "7 yoyos for tract,wedge,wedgePop,r= 7633 3 209701.52301458752 3.0196\n",
      "8 yoyos for tract,wedge,wedgePop,r= 7633 3 123854.01489778465 1.5098\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7633 3 211662.77324619092 3.2045\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7633 3 172993.77857825626 2.3572\n",
      "7 yoyos for tract,wedge,wedgePop,r= 7635 3 199758.09223267253 2.4753\n",
      "8 yoyos for tract,wedge,wedgePop,r= 7635 3 142645.52593714197 1.2377\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7635 3 199415.66434182698 2.4209\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7635 3 160382.9791560922 1.8293\n",
      "11 yoyos for tract,wedge,wedgePop,r= 7635 3 197020.9401857045 2.1251\n",
      "12 yoyos for tract,wedge,wedgePop,r= 7635 3 164888.45521479816 1.9772\n",
      "12 yoyos for tract,wedge,wedgePop,r= 7635 3 184368.6890512428 2.0511\n",
      "13 yoyos for tract,wedge,wedgePop,r= 7635 3 195520.99807667287 2.0881\n",
      "I am working on tract number 7640 of 9129 tracts\n",
      "I am working on tract number 7660 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7662 12.0 0 104.1 0.319 154858.1\n",
      "7 yoyos for tract,wedge,wedgePop,r= 7678 0 223355.21117464697 0.9221\n",
      "8 yoyos for tract,wedge,wedgePop,r= 7678 0 63308.50994054432 0.461\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7678 0 414411.9387339098 0.9955\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7678 0 134604.1886809804 0.7283\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7678 0 161845.34825053197 0.8619\n",
      "11 yoyos for tract,wedge,wedgePop,r= 7678 0 243751.13460518303 0.9287\n",
      "12 yoyos for tract,wedge,wedgePop,r= 7678 0 178481.47634450384 0.8953\n",
      "13 yoyos for tract,wedge,wedgePop,r= 7678 0 201960.5268053665 0.912\n",
      "I am working on tract number 7680 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 7681 0 195624.91414272814 1.2027\n",
      "8 yoyos for tract,wedge,wedgePop,r= 7681 0 102414.50345835832 0.6013\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7681 0 205946.09602233063 1.2494\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7681 0 109435.2885296956 0.9254\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7681 0 114876.94660480642 1.0874\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7681 0 161258.01258962322 1.1684\n",
      "11 yoyos for tract,wedge,wedgePop,r= 7681 0 198407.05312067486 1.2089\n",
      "we have 2 non-opposing shorted wedges for tract no 7684\n",
      "I am working on tract number 7700 of 9129 tracts\n",
      "I am working on tract number 7720 of 9129 tracts\n",
      "I am working on tract number 7740 of 9129 tracts\n",
      "I am working on tract number 7760 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7777 2.0 2 90.0 0.2751 12723.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7777 5.0 0 140.0 0.239 27722.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7778 4.0 0 138.7 0.221 37680.4\n",
      "I am working on tract number 7780 of 9129 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 7787\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7790 4.0 2 90.0 1.1197 192687.8\n",
      "we have 2 non-opposing shorted wedges for tract no 7792\n",
      "we have 2 non-opposing shorted wedges for tract no 7793\n",
      "we have 2 non-opposing shorted wedges for tract no 7794\n",
      "we have 2 non-opposing shorted wedges for tract no 7795\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7796 6.0 0 90.0 1.9541 192812.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7796 7.0 0 90.0 1.9333 192812.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7796 8.0 0 90.0 1.9128 192812.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7796 9.0 0 90.0 1.8924 192812.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7796 10.0 0 90.0 1.8723 192812.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7796 11.0 0 90.0 1.8524 192812.9\n",
      "I am working on tract number 7800 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7814 6.0 0 117.5 0.1831 103133.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7815 3.0 1 90.0 0.3253 78965.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7815 7.0 0 122.2 0.3552 95181.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7816 2.0 1 90.0 0.2079 35600.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7816 5.0 0 131.7 0.1996 54052.6\n",
      "I am working on tract number 7820 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7828 9.0 0 133.2 1.2375 237655.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7828 10.0 0 133.2 1.0414 237655.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7828 11.0 0 133.2 0.8763 237655.7\n",
      "I am working on tract number 7840 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7840 2.0 1 90.0 0.1361 89541.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7840 6.0 0 113.4 0.1974 130810.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7840 7.0 0 113.4 0.2582 130810.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7840 8.0 0 113.4 0.3378 130810.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7840 9.0 0 113.4 0.4419 130810.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7841 4.0 0 143.1 0.6787 3429.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7844 3.0 0 100.4 0.8804 209422.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7844 4.0 0 100.4 0.818 209422.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7844 5.0 0 100.4 0.7599 209422.8\n",
      "7 yoyos for tract,wedge,wedgePop,r= 7845 3 335255.0160397208 1.0251\n",
      "8 yoyos for tract,wedge,wedgePop,r= 7845 3 128395.91743815885 0.5126\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7845 3 337802.03124065907 1.0706\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7845 3 305898.20722573256 0.7916\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7845 3 201972.92151250402 0.6521\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7845 3 145119.31801397583 0.5823\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7845 3 166299.58859797535 0.6172\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7845 3 181489.75297075257 0.6346\n",
      "I am working on tract number 7860 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7874 2.0 2 90.0 0.1539 63171.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7874 6.0 0 119.8 0.3362 110051.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7875 2.0 0 90.0 0.2185 36639.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7875 5.0 0 133.6 0.1982 65725.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7876 4.0 0 143.4 0.9069 4355.3\n",
      "I am working on tract number 7880 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7880 3.0 0 90.0 0.9407 23091.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7882 2.0 0 90.0 0.1394 15814.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7890 3.0 1 90.0 0.485 53393.3\n",
      "I am working on tract number 7900 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7902 4.0 0 132.2 0.2121 70651.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7902 6.0 0 132.2 1.3262 75384.7\n",
      "I am working on tract number 7920 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7924 2.0 1 90.0 0.1621 187125.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7924 3.0 1 90.0 0.164 187125.8\n",
      "I am working on tract number 7940 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7947 5.0 0 90.0 0.3043 155465.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7947 6.0 0 90.0 0.3525 155465.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7947 7.0 0 90.0 0.4085 155465.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7947 8.0 0 90.0 0.4733 155465.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7947 9.0 0 90.0 0.5483 155465.8\n",
      "7 yoyos for tract,wedge,wedgePop,r= 7947 0 281183.1334899737 0.5336\n",
      "8 yoyos for tract,wedge,wedgePop,r= 7947 0 134228.0218810529 0.2668\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7947 0 281183.1334899732 0.5267\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7947 0 240875.0406808833 0.3968\n",
      "loop31.0, tr7947,wedgePops734659.03, 164504.5, 189931.5, 189876.2, 190346.7, Overedge?0, 0, 0, 0, ,Satisfied?0111,yoyo?9001 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,-0.065, 190087.6,0.0003, 190087.6,0.0002, 190087.6,-0.0002\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7947 0 164504.53943142615 0.3318\n",
      "loop32.0, tr7947,wedgePops776226.7, 206072.2, 189931.5, 189876.2, 190346.7, Overedge?0, 0, 0, 0, ,Satisfied?0111,yoyo?10001 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0325, 190087.6,0.0003, 190087.6,0.0002, 190087.6,-0.0002\n",
      "11 yoyos for tract,wedge,wedgePop,r= 7947 0 206072.20701487243 0.3643\n",
      "loop33.0, tr7947,wedgePops755050.1, 184895.6, 189931.5, 189876.2, 190346.7, Overedge?0, 0, 0, 0, ,Satisfied?0111,yoyo?11001 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,-0.0162, 190087.6,0.0003, 190087.6,0.0002, 190087.6,-0.0002\n",
      "12 yoyos for tract,wedge,wedgePop,r= 7947 0 184895.61404886332 0.348\n",
      "loop34.0, tr7947,wedgePops765209.06, 195054.6, 189931.5, 189876.2, 190346.7, Overedge?0, 0, 0, 0, ,Satisfied?0111,yoyo?12001 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0081, 190087.6,0.0003, 190087.6,0.0002, 190087.6,-0.0002\n",
      "13 yoyos for tract,wedge,wedgePop,r= 7947 0 195054.56964953252 0.3562\n",
      "loop35.0, tr7947,wedgePops759964.16, 189809.7, 189931.5, 189876.2, 190346.7, Overedge?0, 0, 0, 0, ,Satisfied?0111,yoyo?13001 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,-0.0041, 190087.6,0.0003, 190087.6,0.0002, 190087.6,-0.0002\n",
      "I am working on tract number 7960 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 7962 3 202630.3983520308 0.7862\n",
      "8 yoyos for tract,wedge,wedgePop,r= 7962 3 47422.22207318604 0.3931\n",
      "9 yoyos for tract,wedge,wedgePop,r= 7962 3 336423.96987126605 0.8298\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7962 3 88442.98034695248 0.6114\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7962 3 108326.7447559385 0.7206\n",
      "10 yoyos for tract,wedge,wedgePop,r= 7962 3 172809.95207793513 0.7752\n",
      "11 yoyos for tract,wedge,wedgePop,r= 7962 3 254955.73566012864 0.8025\n",
      "11 yoyos for tract,wedge,wedgePop,r= 7962 3 210560.34220498774 0.7888\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7967 10.0 1 56.0 3.1209 367131.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 7967 19.0 1 56.0 3.1753 367131.9\n",
      "7 yoyos for tract,wedge,wedgePop,r= 7967 1 367131.9125149366 3.4488\n",
      "I am working on tract number 7980 of 9129 tracts\n",
      "I am working on tract number 8000 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8007 2.0 0 90.0 0.1799 41867.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8007 7.0 0 129.2 1.0758 68005.6\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8018 3 687516.4434750963 0.9135\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8018 3 77366.8256292874 0.4568\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8018 3 1439759.2106238655 1.2427\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8018 3 359204.25282332604 0.8497\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8018 3 106945.21598625337 0.6532\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8018 3 115414.09465714458 0.7515\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8018 3 182610.8501552266 0.8006\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8018 3 257774.08353879012 0.8252\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8018 3 214437.07718109302 0.8129\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8018 3 198936.87587633095 0.8067\n",
      "I am working on tract number 8020 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8022 9.0 0 115.3 0.4576 238477.1\n",
      "I am working on tract number 8040 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8045 7.0 2 90.0 0.3973 185993.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8045 8.0 2 90.0 0.4038 185993.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8045 9.0 2 90.0 0.4104 185993.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8045 10.0 2 90.0 0.4172 185993.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8045 11.0 2 90.0 0.424 185993.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8045 12.0 2 90.0 0.431 185993.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8045 13.0 2 90.0 0.4381 185993.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8045 14.0 2 90.0 0.4452 185993.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8045 15.0 2 90.0 0.4526 185993.8\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8047 1 202106.13931653358 0.4059\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8047 1 100425.3124949721 0.203\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8047 1 239659.90042795852 0.465\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8047 1 110832.683531527 0.334\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8047 1 198205.39736248535 0.3995\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8047 1 139946.91271266108 0.3667\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8047 1 175018.54401897063 0.3831\n",
      "I am working on tract number 8060 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8076 4.0 0 137.0 0.2016 47720.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8076 5.0 0 137.0 0.5029 47720.0\n",
      "I am working on tract number 8080 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8080 4.0 2 90.0 0.2105 147778.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8080 5.0 2 90.0 0.2528 147778.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8080 6.0 2 90.0 0.3037 147778.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8080 7.0 2 90.0 0.3648 147778.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8097 4.0 3 90.0 0.7081 148811.9\n",
      "I am working on tract number 8100 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8116 3 1554734.3111158072 2.632\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8116 3 533111.6443752177 1.316\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8116 3 14864.896542977134 0.658\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8116 3 390840.3010881928 1.2607\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8116 3 25866.31221367675 0.9593\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8116 3 58226.71724421392 1.11\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8116 3 170229.96850671683 1.1854\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8116 3 294254.3391902465 1.223\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8116 3 234849.28264813885 1.2042\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8116 3 199347.39481179958 1.1948\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8116 3 184045.58336667938 1.1901\n",
      "I am working on tract number 8120 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8126 2.0 0 90.0 0.3992 365505.3\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8126 2 254314.27236791718 1.3092\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8126 2 14222.774393306783 0.6546\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8126 2 733339.8947990389 1.5067\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8126 2 49061.93121787836 1.0806\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8126 2 201839.87681824228 1.2936\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8126 2 56463.845014408056 1.1871\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8126 2 77815.26871090033 1.2404\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8126 2 120989.49812641834 1.267\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8126 2 155752.31605863236 1.2803\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8126 2 177336.89200860666 1.287\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8129 7.0 0 109.5 0.5923 279614.9\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8129 0 262078.2345581556 0.4529\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8129 0 75654.43102350028 0.2264\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8129 0 278022.01505249133 0.4783\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8129 0 103037.02461179605 0.3524\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8132 3.0 0 90.0 0.7666 81224.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8132 8.0 0 87.0 0.4808 178117.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8132 9.0 0 87.0 0.5046 178117.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8132 10.0 0 87.0 0.5296 178117.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8132 11.0 0 87.0 0.5559 178117.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8132 12.0 0 87.0 0.5834 178117.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8132 13.0 0 87.0 0.6124 178117.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8132 14.0 0 87.0 0.6427 178117.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8132 15.0 0 87.0 0.6746 178117.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8132 16.0 0 87.0 0.708 178117.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8132 17.0 0 87.0 0.7431 178117.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8132 18.0 0 87.0 0.78 178117.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8132 19.0 0 87.0 0.8187 178117.8\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8135 3 288073.56410417624 1.8764\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8135 3 73924.22068930912 0.9382\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8135 3 288044.34609748307 1.8761\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8135 3 113503.97693988486 1.4072\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8135 3 254616.62426906519 1.6416\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8135 3 133752.8708111769 1.5244\n",
      "13 yoyos for tract,wedge,wedgePop,r= 8135 3 211461.34993238014 1.583\n",
      "14 yoyos for tract,wedge,wedgePop,r= 8135 3 166849.81684239657 1.5537\n",
      "I am working on tract number 8140 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8147 2.0 0 90.0 0.6727 342268.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8147 3.0 0 90.0 0.4156 342268.6\n",
      "I am working on tract number 8160 of 9129 tracts\n",
      "I am working on tract number 8180 of 9129 tracts\n",
      "I am working on tract number 8200 of 9129 tracts\n",
      "I am working on tract number 8220 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8230 8.0 1 90.0 0.2307 184870.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8230 9.0 1 90.0 0.2355 184870.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8230 10.0 1 90.0 0.2405 184870.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8230 11.0 1 90.0 0.2455 184870.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8230 12.0 1 90.0 0.2507 184870.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8230 13.0 1 90.0 0.2559 184870.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8230 14.0 1 90.0 0.2613 184870.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8230 15.0 1 90.0 0.2668 184870.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8230 16.0 1 90.0 0.2724 184870.7\n",
      "I am working on tract number 8240 of 9129 tracts\n",
      "I am working on tract number 8260 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8266 4.0 1 90.0 1.01 95203.2\n",
      "I am working on tract number 8280 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8287 3 12271.616000209237 2.3963\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8287 3 1582086.6990069975 10.0232\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8287 3 1399553.6159547332 6.2097\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8287 3 615375.9304373082 4.303\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8287 3 57908.72681427421 3.3496\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8287 3 333032.88735522964 3.8263\n",
      "loop31.0, tr8287,wedgePops629608.71, 182005.0, 192692.0, 192689.7, 62222.0, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?01110 \n",
      "   targetWP, latest drx4 are tWP,dr, 192781.8,0.9104, 192781.8,0.0005, 192781.8,0.0003, 192781.8,-0.2383\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8287 3 62221.986735624785 3.588\n",
      "loop32.0, tr8287,wedgePops688280.71, 182005.0, 192692.0, 192689.7, 120894.0, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?01111 \n",
      "   targetWP, latest drx4 are tWP,dr, 192781.8,0.9104, 192781.8,0.0005, 192781.8,0.0003, 192781.8,0.1192\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8287 3 120893.98357717526 3.7072\n",
      "loop33.0, tr8287,wedgePops780158.63, 182005.0, 192692.0, 192689.7, 212771.9, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?01111 \n",
      "   targetWP, latest drx4 are tWP,dr, 192781.8,0.9104, 192781.8,0.0005, 192781.8,0.0003, 192781.8,0.0596\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8287 3 212771.90576933546 3.7667\n",
      "loop34.0, tr8287,wedgePops725962.51, 182005.0, 192692.0, 192689.7, 158575.8, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?01112 \n",
      "   targetWP, latest drx4 are tWP,dr, 192781.8,0.9104, 192781.8,0.0005, 192781.8,0.0003, 192781.8,-0.0298\n",
      "13 yoyos for tract,wedge,wedgePop,r= 8287 3 158575.78866053442 3.7369\n",
      "loop35.0, tr8287,wedgePops754500.72, 182005.0, 192692.0, 192689.7, 187114.0, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?01113 \n",
      "   targetWP, latest drx4 are tWP,dr, 192781.8,0.9104, 192781.8,0.0005, 192781.8,0.0003, 192781.8,0.0149\n",
      "13 yoyos for tract,wedge,wedgePop,r= 8287 3 187113.99648560898 3.7518\n",
      "loop36.0, tr8287,wedgePops768216.82, 182005.0, 192692.0, 192689.7, 200830.1, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?01113 \n",
      "   targetWP, latest drx4 are tWP,dr, 192781.8,0.9104, 192781.8,0.0005, 192781.8,0.0003, 192781.8,0.0074\n",
      "14 yoyos for tract,wedge,wedgePop,r= 8287 3 200830.09257027291 3.7593\n",
      "loop37.0, tr8287,wedgePops761446.14, 182005.0, 192692.0, 192689.7, 194059.4, Overedge?1, 0, 0, 0, ,Satisfied?0110,yoyo?01114 \n",
      "   targetWP, latest drx4 are tWP,dr, 192781.8,0.9104, 192781.8,0.0005, 192781.8,0.0003, 192781.8,-0.0037\n",
      "I am working on tract number 8300 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8309 3 205188.90810119352 0.6242\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8309 3 141766.8441449675 0.3121\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8309 3 234975.20846491825 0.9368\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8309 3 205427.66164685943 0.6245\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8309 3 165659.21456950277 0.4683\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8309 3 165876.66034553695 0.5464\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8309 3 176104.0021908029 0.5854\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8309 3 186245.49362617053 0.6049\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8309 3 195860.50350086048 0.6147\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8314 1 242672.20296494884 0.8824\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8314 1 96962.87268091069 0.4412\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8314 1 238379.69837461697 0.8623\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8314 1 130700.45414098095 0.6518\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8314 1 224034.43099645 0.757\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8314 1 162667.4468549811 0.7044\n",
      "13 yoyos for tract,wedge,wedgePop,r= 8314 1 196753.9409014425 0.7307\n",
      "14 yoyos for tract,wedge,wedgePop,r= 8314 1 179448.66095772182 0.7176\n",
      "I am working on tract number 8320 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8323 7.0 3 90.0 0.5105 212385.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8330 4.0 1 90.0 0.2743 139588.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8330 5.0 1 90.0 0.3429 139588.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8330 9.0 0 112.2 0.1984 118587.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8330 10.0 0 112.2 0.2776 118587.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8331 3.0 0 112.2 0.8074 249122.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8331 4.0 0 112.2 0.6542 249122.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8331 5.0 0 112.2 0.5301 249122.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8334 6.0 0 83.3 0.5064 171396.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8334 7.0 0 83.3 0.5467 171396.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8334 8.0 0 83.3 0.5903 171396.0\n",
      "I am working on tract number 8340 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8345 0 228194.76680547514 2.5435\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8345 0 110256.75478028579 1.2718\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8345 0 228201.09795108883 2.5437\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8345 0 137770.99659472593 1.9077\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8345 0 210729.6396996274 2.2257\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8345 0 163622.08526486903 2.0667\n",
      "I am working on tract number 8360 of 9129 tracts\n",
      "I am working on tract number 8380 of 9129 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 8385\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8395 13.0 3 33.4 2.934 228973.0\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8399 2 235031.29746971757 3.1061\n",
      "I am working on tract number 8400 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8402 3 262123.65875876945 3.968\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8402 3 102090.6849025744 1.984\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8402 3 262123.65875876945 3.947\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8402 3 231663.53218034166 2.9655\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8402 3 119192.97870105939 2.4747\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8402 3 139235.48086348188 2.7201\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8402 3 161050.91585486606 2.8428\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8404 3 197803.10534894903 2.6189\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8404 3 62376.06190437544 1.3095\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8404 3 200586.0518319994 2.9234\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8404 3 83518.79226882695 2.1164\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8404 3 176768.66233899066 2.5199\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8404 3 199134.39876760688 2.7216\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8404 3 197832.47906232573 2.6207\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8404 3 194123.59232622109 2.5703\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8412 14.0 0 97.0 2.6611 191892.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8412 15.0 0 97.0 2.6422 191892.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8414 15.0 0 93.9 2.6383 196772.1\n",
      "I am working on tract number 8420 of 9129 tracts\n",
      "I am working on tract number 8440 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8443 14.0 0 84.5 2.3354 190767.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8443 15.0 0 84.5 2.3292 190767.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8443 16.0 0 84.5 2.323 190767.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8443 17.0 0 84.5 2.3168 190767.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8443 18.0 0 84.5 2.3106 190767.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8443 19.0 0 84.5 2.3044 190767.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8443 20.0 0 84.5 2.2982 190767.1\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8447 3 614509.1187849327 4.2693\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8447 3 86911.52342071058 2.1347\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8447 3 617592.7747599953 4.3232\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8447 3 185865.0441818193 3.2289\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8447 3 539982.4430970958 3.7761\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8447 3 462497.6304515082 3.5025\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8447 3 347101.3010931791 3.3657\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8447 3 256212.10877607466 3.2973\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8447 3 212046.61446948367 3.2631\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8447 3 197949.52116018973 3.246\n",
      "I am working on tract number 8460 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8468 6.0 0 130.1 0.5683 43386.6\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8474 1 201182.66650099016 1.3826\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8474 1 19662.829364994774 0.6913\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8474 1 262688.35303545656 1.4162\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8474 1 85707.2485413054 1.0538\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8474 1 135887.33188793465 1.235\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8474 1 144133.17108284694 1.3256\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8474 1 180712.1806761949 1.3709\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8474 1 217190.39087238588 1.3936\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8474 1 200738.62246966513 1.3823\n",
      "I am working on tract number 8480 of 9129 tracts\n",
      "I am working on tract number 8500 of 9129 tracts\n",
      "I am working on tract number 8520 of 9129 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 8521\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8525 1 231286.51156491684 1.1255\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8525 1 1047596.3300956959 3.0195\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8525 1 878457.1877171333 2.0725\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8525 1 480081.773804407 1.599\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8525 1 467913.43081030966 1.3623\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8525 1 411509.00871295587 1.2439\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8525 1 347225.88430117373 1.1847\n",
      "loop31.0, tr8525,wedgePops795575.94, 58786.3, 287057.2, 251120.0, 198612.5, Overedge?1, 0, 0, 1, ,Satisfied?0010,yoyo?0800 \n",
      "   targetWP, latest drx4 are tWP,dr, 251475.8,0.9104, 251475.8,-0.0296, 251475.8,0.0013, 251475.8,0.9104\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8525 1 287057.1920723328 1.1551\n",
      "loop32.0, tr8525,wedgePops766678.73, 58786.3, 258160.0, 251120.0, 198612.5, Overedge?1, 0, 0, 1, ,Satisfied?0010,yoyo?0800 \n",
      "   targetWP, latest drx4 are tWP,dr, 251475.8,0.9104, 251475.8,-0.0148, 251475.8,0.0013, 251475.8,0.9104\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8525 1 258159.97927492336 1.1403\n",
      "loop33.0, tr8525,wedgePops752773.31, 58786.3, 244254.6, 251120.0, 198612.5, Overedge?1, 0, 0, 1, ,Satisfied?0010,yoyo?0800 \n",
      "   targetWP, latest drx4 are tWP,dr, 251475.8,0.9104, 251475.8,-0.0074, 251475.8,0.0013, 251475.8,0.9104\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8525 1 244254.55928239785 1.1329\n",
      "loop34.0, tr8525,wedgePops759571.83, 58786.3, 251053.1, 251120.0, 198612.5, Overedge?1, 0, 0, 1, ,Satisfied?0010,yoyo?0900 \n",
      "   targetWP, latest drx4 are tWP,dr, 251475.8,0.9104, 251475.8,0.0037, 251475.8,0.0013, 251475.8,0.9104\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8527 0 193151.9882498496 2.2959\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8527 0 100434.40944355656 1.148\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8527 0 327318.9345651427 2.6222\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8527 0 156165.36180647323 1.8851\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8527 0 168019.96863622373 2.2536\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8527 0 252046.5920761369 2.4379\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8527 0 239295.44989882718 2.3458\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8527 0 198278.28930688897 2.2997\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8527 0 171978.12066331503 2.2767\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8527 0 183526.66393269127 2.2882\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8538 6.0 0 95.4 0.3363 171982.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8538 7.0 0 95.4 0.3622 171982.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8538 8.0 0 95.4 0.3901 171982.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8538 9.0 0 95.4 0.4201 171982.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8538 10.0 0 95.4 0.4525 171982.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8538 11.0 0 95.4 0.4873 171982.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8538 12.0 0 95.4 0.5248 171982.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8539 8.0 0 87.6 0.3561 57014.0\n",
      "I am working on tract number 8540 of 9129 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 8544\n",
      "we have 2 non-opposing shorted wedges for tract no 8545\n",
      "we have 2 non-opposing shorted wedges for tract no 8557\n",
      "I am working on tract number 8560 of 9129 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 8560\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8573 3 473071.96788212715 1.64\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8573 3 87402.71403190575 0.82\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8573 3 450850.2781629397 1.5857\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8573 3 155922.004704559 1.2029\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8573 3 329593.83364454255 1.3943\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8573 3 304555.1634693384 1.2986\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8573 3 241341.79614912986 1.2507\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8578 3.0 3 67.9 0.375 163300.3\n",
      "I am working on tract number 8580 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8585 0 309339.7084405613 1.5517\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8585 0 110651.276108202 0.7758\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8585 0 305582.6574051202 1.4402\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8585 0 242460.6703067782 1.108\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8585 0 116549.85336974221 0.9419\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8585 0 159010.04256952813 1.025\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8585 0 205510.8594982187 1.0665\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8585 0 181152.04832583043 1.0457\n",
      "13 yoyos for tract,wedge,wedgePop,r= 8585 0 193863.9545157018 1.0561\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8599 3 697807.7123900517 1.4441\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8599 3 172836.00489786 0.722\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8599 3 695204.9801382383 1.436\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8599 3 650580.2244091579 1.079\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8599 3 475718.80198411725 0.9005\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8599 3 369234.29144443147 0.8113\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8599 3 295225.2368855672 0.7667\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8599 3 241393.81373928903 0.7444\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8599 3 209822.06492200997 0.7332\n",
      "I am working on tract number 8600 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 3.0 0 140.7 0.8973 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 3.0 3 39.3 0.5427 779462.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 4.0 0 140.7 0.8702 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 5.0 0 140.7 0.8438 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 6.0 0 140.7 0.8183 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 7.0 0 140.7 0.7958 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 8.0 0 140.7 0.774 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 9.0 0 140.7 0.7527 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 10.0 0 140.7 0.732 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 11.0 0 140.7 0.7119 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 12.0 0 140.7 0.6924 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 13.0 0 140.7 0.6734 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 14.0 0 140.7 0.6549 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 15.0 0 140.7 0.6369 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 16.0 0 140.7 0.6194 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 17.0 0 140.7 0.6024 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 18.0 0 140.7 0.5858 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 19.0 0 140.7 0.5697 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 20.0 0 140.7 0.5541 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 21.0 0 140.7 0.5389 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 22.0 0 140.7 0.5241 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 23.0 0 140.7 0.5097 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 24.0 0 140.7 0.4957 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 25.0 0 140.7 0.4821 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 26.0 0 140.7 0.4688 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 27.0 0 140.7 0.4559 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 28.0 0 140.7 0.4434 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 29.0 0 140.7 0.4312 197999.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 30.0 0 140.7 0.4194 197999.4\n",
      "loop31.0, tr8616,wedgePops767387.03, 197999.4, 187905.1, 190542.5, 190940.0, Overedge?0, 1, 0, 0, ,Satisfied?0011,yoyo?0002 \n",
      "   targetWP, latest drx4 are tWP,dr, 190815.1,-0.0115, 190815.1,-0.3592, 190815.1,0.0004, 190815.1,-0.0001\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 31.0 0 140.7 0.4079 197999.4\n",
      "loop32.0, tr8616,wedgePops767387.03, 197999.4, 187905.1, 190542.5, 190940.0, Overedge?0, 1, 0, 0, ,Satisfied?0011,yoyo?0002 \n",
      "   targetWP, latest drx4 are tWP,dr, 190815.1,-0.0112, 190815.1,-0.3592, 190815.1,0.0004, 190815.1,-0.0001\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 32.0 0 140.7 0.3967 197999.4\n",
      "loop33.0, tr8616,wedgePops767387.03, 197999.4, 187905.1, 190542.5, 190940.0, Overedge?0, 1, 0, 0, ,Satisfied?0011,yoyo?0002 \n",
      "   targetWP, latest drx4 are tWP,dr, 190815.1,-0.0109, 190815.1,-0.3592, 190815.1,0.0004, 190815.1,-0.0001\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8616 33.0 0 140.7 0.3858 197999.4\n",
      "loop34.0, tr8616,wedgePops766128.77, 196741.2, 187905.1, 190542.5, 190940.0, Overedge?0, 1, 0, 0, ,Satisfied?0011,yoyo?0002 \n",
      "   targetWP, latest drx4 are tWP,dr, 190815.1,-0.0106, 190815.1,-0.3592, 190815.1,0.0004, 190815.1,-0.0001\n",
      "loop35.0, tr8616,wedgePops749300.73, 179913.1, 187905.1, 190542.5, 190940.0, Overedge?0, 1, 0, 0, ,Satisfied?0011,yoyo?0002 \n",
      "   targetWP, latest drx4 are tWP,dr, 190815.1,-0.0437, 190815.1,-0.3592, 190815.1,0.0004, 190815.1,-0.0001\n",
      "loop36.0, tr8616,wedgePops759048.12, 189660.5, 187905.1, 190542.5, 190940.0, Overedge?0, 1, 0, 0, ,Satisfied?0011,yoyo?1002 \n",
      "   targetWP, latest drx4 are tWP,dr, 190815.1,0.0231, 190815.1,-0.3592, 190815.1,0.0004, 190815.1,-0.0001\n",
      "I am working on tract number 8620 of 9129 tracts\n",
      "I am working on tract number 8640 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8649 0 559497.1316381698 1.1245\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8649 0 105950.82135566865 0.5622\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8649 0 559458.6241316891 1.1242\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8649 0 517794.8009637982 0.8432\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8649 0 342533.5742809799 0.7027\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8649 0 266629.7603944682 0.6325\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8649 0 157704.93647370872 0.5974\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8649 0 213006.81354814404 0.6149\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8649 0 181971.27402274776 0.6061\n",
      "13 yoyos for tract,wedge,wedgePop,r= 8649 0 197064.5347304532 0.6105\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8650 0 346425.60326280014 0.6769\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8650 0 109671.28357736769 0.3384\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8650 0 489013.87866676226 0.761\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8650 0 125152.96862216538 0.5497\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8650 0 325144.6961580513 0.6554\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8650 0 203199.6918455179 0.6026\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8650 0 140310.85960882358 0.5761\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8650 0 163364.4497138584 0.5893\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8650 0 181658.5829293747 0.5959\n",
      "we have 2 non-opposing shorted wedges for tract no 8652\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8659 0 196139.9615979611 0.9196\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8659 0 73629.01775931132 0.4598\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8659 0 236460.7323704473 1.0143\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8659 0 96778.31549710495 0.737\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8659 0 141732.5466318706 0.8757\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8659 0 220930.4875145965 0.945\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8659 0 184679.66944044305 0.9103\n",
      "13 yoyos for tract,wedge,wedgePop,r= 8659 0 206038.3595204744 0.9276\n",
      "13 yoyos for tract,wedge,wedgePop,r= 8659 0 195294.52331112756 0.919\n",
      "I am working on tract number 8660 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8661 1 262272.75457278965 1.0754\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8661 1 84357.37702849958 0.5377\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8661 1 265699.06739370193 1.1046\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8661 1 116567.8003513192 0.8212\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8661 1 247080.75475677924 0.9629\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8671 4.0 0 90.0 1.0173 93445.1\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8676 3 202586.3109899329 1.0988\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8676 3 159560.382802775 0.5494\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8676 3 202566.08242851496 1.0978\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8676 3 168885.747505171 0.8236\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8676 3 196274.690266293 0.9607\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8676 3 175009.02655707402 0.8921\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8676 3 184438.65259246452 0.9264\n",
      "I am working on tract number 8680 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8680 1 272485.43392170663 1.3112\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8680 1 96545.35065869437 0.6556\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8680 1 260572.91544026817 1.1774\n",
      "I am working on tract number 8700 of 9129 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 8718\n",
      "I am working on tract number 8720 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8723 4.0 0 112.4 0.442 9189.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8728 8.0 1 -272.4 0.2664 121233.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8729 15.0 1 -272.4 1.2483 217572.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8729 16.0 1 -272.4 1.1261 217572.0\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8729 1 217572.02158874157 1.2225\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8729 1 118646.05253381675 0.6113\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8729 1 311110.576321316 1.7678\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8729 1 217572.0215887567 1.1895\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8729 1 121560.39726415931 0.9004\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8729 1 217572.02158876107 1.045\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8729 1 166994.37576909704 0.9727\n",
      "13 yoyos for tract,wedge,wedgePop,r= 8729 1 208099.46529060684 1.0088\n",
      "loop31.0, tr8729,wedgePops762171.34, 189948.2, 192218.5, 189799.3, 190205.3, Overedge?0, 0, 0, 0, ,Satisfied?1011,yoyo?01321 \n",
      "   targetWP, latest drx4 are tWP,dr, 190087.6,0.0002, 190087.6,-0.0181, 190087.6,0.0184, 190087.6,-0.0001\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8730 3.0 1 90.0 0.201 95971.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8730 4.0 1 90.0 0.3239 95971.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8733 5.0 2 90.0 0.2713 145917.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8734 6.0 3 90.0 0.2445 175068.9\n",
      "I am working on tract number 8740 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8754 2.0 1 90.0 0.614 4005.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8755 6.0 2 452.4 0.7122 30042.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8756 8.0 2 452.4 0.191 84259.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8756 9.0 2 452.4 0.3348 84259.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8757 7.0 2 452.4 0.2895 58025.8\n",
      "I am working on tract number 8760 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8765 1 235636.46006535084 3.2282\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8765 1 89607.47219947455 1.6141\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8765 1 238381.3603936623 3.5113\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8765 1 118477.90812800334 2.5627\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8765 1 232163.22690997698 3.037\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8765 1 143692.1452868686 2.7999\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8765 1 182983.4143218918 2.9184\n",
      "13 yoyos for tract,wedge,wedgePop,r= 8765 1 222148.03315089762 2.9777\n",
      "13 yoyos for tract,wedge,wedgePop,r= 8765 1 209279.4751085912 2.9481\n",
      "13 yoyos for tract,wedge,wedgePop,r= 8765 1 197330.71062806936 2.9333\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8768 8.0 2 90.0 0.927 287092.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8770 2.0 2 90.0 1.0273 296.0\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8770 2 862001.3530326895 5.2349\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8770 2 390826.1700974554 2.6174\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8770 2 60614.13227795606 1.3087\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8770 2 375189.79383647017 2.4856\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8770 2 65990.40538686089 1.8971\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8770 2 283247.1941834731 2.1914\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8770 2 71321.33150714755 2.0442\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8770 2 91528.84709059432 2.1178\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8770 2 167825.43904504285 2.1546\n",
      "13 yoyos for tract,wedge,wedgePop,r= 8770 2 233834.79842342518 2.173\n",
      "13 yoyos for tract,wedge,wedgePop,r= 8770 2 201315.8390019658 2.1638\n",
      "14 yoyos for tract,wedge,wedgePop,r= 8770 2 183960.32121737674 2.1592\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8771 5.0 2 452.4 0.1343 48784.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8772 4.0 2 452.4 0.2407 6824.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8774 4.0 0 143.2 0.9275 4918.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8774 4.0 3 36.8 0.5127 17179.1\n",
      "I am working on tract number 8780 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8786 2.0 1 90.0 0.2875 16437.1\n",
      "I am working on tract number 8800 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8808 1 8077.506581747788 0.7473\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8808 1 2533519.8041759566 3.2524\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8808 1 1008362.4535521297 1.9998\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8808 1 606683.2225827449 1.3736\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8808 1 191940.82074780372 1.0604\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8808 1 548290.8150453661 1.217\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8808 1 428442.97649260523 1.1387\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8808 1 329477.2438097437 1.0996\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8808 1 269557.78943887196 1.08\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8808 1 231376.5494177527 1.0702\n",
      "loop31.0, tr8808,wedgePops751911.73, 100573.2, 211604.0, 219771.2, 219963.3, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01001 \n",
      "   targetWP, latest drx4 are tWP,dr, 219925.7,0.9104, 219925.7,-0.0049, 219925.7,0.0006, 219925.7,0.0023\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8808 1 211604.0247859424 1.0653\n",
      "loop32.0, tr8808,wedgePops761715.32, 100573.2, 221407.6, 219771.2, 219963.3, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?01101 \n",
      "   targetWP, latest drx4 are tWP,dr, 219925.7,0.9104, 219925.7,0.0024, 219925.7,0.0006, 219925.7,0.0023\n",
      "I am working on tract number 8820 of 9129 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 8821\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8831 5.0 0 90.0 1.0218 240639.8\n",
      "I am working on tract number 8840 of 9129 tracts\n",
      "need to widen edge circle beyond 0.0006027675587071863 for tract (x,y)=( -122.33111118205689 37.57972823697045\n",
      "need to widen edge circle beyond 0.0006630443145779051 for tract (x,y)=( -122.33111118205689 37.57972823697045\n",
      "need to widen edge circle beyond 0.0007293487460356957 for tract (x,y)=( -122.33111118205689 37.57972823697045\n",
      "need to widen edge circle beyond 0.0008022836206392653 for tract (x,y)=( -122.33111118205689 37.57972823697045\n",
      "need to widen edge circle beyond 0.0008825119827031919 for tract (x,y)=( -122.33111118205689 37.57972823697045\n",
      "need to widen edge circle beyond 0.0009707631809735112 for tract (x,y)=( -122.33111118205689 37.57972823697045\n",
      "need to widen edge circle beyond 0.0010678394990708624 for tract (x,y)=( -122.33111118205689 37.57972823697045\n",
      "need to widen edge circle beyond 0.0011746234489779489 for tract (x,y)=( -122.33111118205689 37.57972823697045\n",
      "need to widen edge circle beyond 0.001292085793875744 for tract (x,y)=( -122.33111118205689 37.57972823697045\n",
      "need to widen edge circle beyond 0.0014212943732633185 for tract (x,y)=( -122.33111118205689 37.57972823697045\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "need to widen edge circle beyond 0.0007776545556591054 for tract (x,y)=( -122.31933948923351 37.56534934039435\n",
      "need to widen edge circle beyond 0.0008554200112250161 for tract (x,y)=( -122.31933948923351 37.56534934039435\n",
      "need to widen edge circle beyond 0.0009409620123475178 for tract (x,y)=( -122.31933948923351 37.56534934039435\n",
      "need to widen edge circle beyond 0.0010350582135822697 for tract (x,y)=( -122.31933948923351 37.56534934039435\n",
      "need to widen edge circle beyond 0.0011385640349404968 for tract (x,y)=( -122.31933948923351 37.56534934039435\n",
      "need to widen edge circle beyond 0.0012524204384345467 for tract (x,y)=( -122.31933948923351 37.56534934039435\n",
      "need to widen edge circle beyond 0.0013776624822780014 for tract (x,y)=( -122.31933948923351 37.56534934039435\n",
      "need to widen edge circle beyond 0.0015154287305058016 for tract (x,y)=( -122.31933948923351 37.56534934039435\n",
      "need to widen edge circle beyond 0.001666971603556382 for tract (x,y)=( -122.31933948923351 37.56534934039435\n",
      "need to widen edge circle beyond 0.0018336687639120203 for tract (x,y)=( -122.31933948923351 37.56534934039435\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "I am working on tract number 8860 of 9129 tracts\n",
      "need to widen edge circle beyond 0.0006557366610689737 for tract (x,y)=( -122.32562096659213 37.56138209408391\n",
      "need to widen edge circle beyond 0.0007213103271758712 for tract (x,y)=( -122.32562096659213 37.56138209408391\n",
      "need to widen edge circle beyond 0.0007934413598934584 for tract (x,y)=( -122.32562096659213 37.56138209408391\n",
      "need to widen edge circle beyond 0.0008727854958828044 for tract (x,y)=( -122.32562096659213 37.56138209408391\n",
      "need to widen edge circle beyond 0.0009600640454710849 for tract (x,y)=( -122.32562096659213 37.56138209408391\n",
      "need to widen edge circle beyond 0.0010560704500181934 for tract (x,y)=( -122.32562096659213 37.56138209408391\n",
      "need to widen edge circle beyond 0.001161677495020013 for tract (x,y)=( -122.32562096659213 37.56138209408391\n",
      "need to widen edge circle beyond 0.0012778452445220143 for tract (x,y)=( -122.32562096659213 37.56138209408391\n",
      "need to widen edge circle beyond 0.001405629768974216 for tract (x,y)=( -122.32562096659213 37.56138209408391\n",
      "need to widen edge circle beyond 0.0015461927458716377 for tract (x,y)=( -122.32562096659213 37.56138209408391\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8861 10.0 1 92.5 1.0389 159290.5\n",
      "need to widen edge circle beyond 0.000758556145929789 for tract (x,y)=( -122.2618940130163 37.561236753234105\n",
      "need to widen edge circle beyond 0.000834411760522768 for tract (x,y)=( -122.2618940130163 37.561236753234105\n",
      "need to widen edge circle beyond 0.0009178529365750449 for tract (x,y)=( -122.2618940130163 37.561236753234105\n",
      "need to widen edge circle beyond 0.0010096382302325494 for tract (x,y)=( -122.2618940130163 37.561236753234105\n",
      "need to widen edge circle beyond 0.0011106020532558043 for tract (x,y)=( -122.2618940130163 37.561236753234105\n",
      "need to widen edge circle beyond 0.001221662258581385 for tract (x,y)=( -122.2618940130163 37.561236753234105\n",
      "need to widen edge circle beyond 0.0013438284844395235 for tract (x,y)=( -122.2618940130163 37.561236753234105\n",
      "need to widen edge circle beyond 0.0014782113328834759 for tract (x,y)=( -122.2618940130163 37.561236753234105\n",
      "need to widen edge circle beyond 0.0016260324661718237 for tract (x,y)=( -122.2618940130163 37.561236753234105\n",
      "need to widen edge circle beyond 0.0017886357127890062 for tract (x,y)=( -122.2618940130163 37.561236753234105\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8875 16.0 0 95.4 4.0662 255305.5\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8875 0 254529.31701124852 3.976\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8875 0 92235.7214839542 1.988\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8875 0 255305.46212015025 4.0655\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8875 0 137328.76861404814 3.0268\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8875 0 148636.96202093773 3.5461\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8875 0 189265.64037251638 3.8058\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8875 0 252782.17397046954 3.9357\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8875 0 234081.1766946369 3.8707\n",
      "13 yoyos for tract,wedge,wedgePop,r= 8875 0 251072.18734301956 3.9032\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8879 8.0 3 54.1 0.8098 139254.7\n",
      "I am working on tract number 8880 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8884 3 265233.0644540158 0.9211\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8884 3 70532.6887248017 0.4605\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8884 3 267930.4011225582 0.9546\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8884 3 122419.99363887499 0.7076\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8884 3 259577.0792448816 0.8311\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8884 3 179313.4499574845 0.7693\n",
      "13 yoyos for tract,wedge,wedgePop,r= 8884 3 243608.43687358912 0.8002\n",
      "13 yoyos for tract,wedge,wedgePop,r= 8884 3 215035.86797635013 0.7848\n",
      "13 yoyos for tract,wedge,wedgePop,r= 8884 3 197652.6206904412 0.7771\n",
      "need to widen edge circle beyond 0.0018643456577573292 for tract (x,y)=( -122.3457498095895 37.51999789589392\n",
      "need to widen edge circle beyond 0.002050780223533062 for tract (x,y)=( -122.3457498095895 37.51999789589392\n",
      "need to widen edge circle beyond 0.0022558582458863685 for tract (x,y)=( -122.3457498095895 37.51999789589392\n",
      "need to widen edge circle beyond 0.0024814440704750054 for tract (x,y)=( -122.3457498095895 37.51999789589392\n",
      "need to widen edge circle beyond 0.002729588477522506 for tract (x,y)=( -122.3457498095895 37.51999789589392\n",
      "need to widen edge circle beyond 0.003002547325274757 for tract (x,y)=( -122.3457498095895 37.51999789589392\n",
      "need to widen edge circle beyond 0.003302802057802233 for tract (x,y)=( -122.3457498095895 37.51999789589392\n",
      "need to widen edge circle beyond 0.003633082263582457 for tract (x,y)=( -122.3457498095895 37.51999789589392\n",
      "need to widen edge circle beyond 0.003996390489940702 for tract (x,y)=( -122.3457498095895 37.51999789589392\n",
      "need to widen edge circle beyond 0.004396029538934773 for tract (x,y)=( -122.3457498095895 37.51999789589392\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 9.0 1 43.0 0.9282 218248.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 10.0 1 43.0 0.9493 218248.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 11.0 1 43.0 0.9708 218248.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 12.0 1 43.0 0.9928 218248.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 13.0 1 43.0 1.0153 218248.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 14.0 1 43.0 1.0384 218248.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 15.0 1 43.0 1.0619 218248.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 16.0 1 43.0 1.086 218248.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 17.0 1 43.0 1.1106 218248.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 18.0 1 43.0 1.1358 218248.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 19.0 1 43.0 1.1615 218248.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 25.0 1 43.0 1.0401 218248.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 26.0 1 43.0 1.0636 218248.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 27.0 1 43.0 1.0878 218248.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 28.0 1 43.0 1.1124 218248.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 29.0 1 43.0 1.1377 218248.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 30.0 1 43.0 1.1634 218248.7\n",
      "loop31.0, tr8891,wedgePops753332.94, 85659.1, 218289.8, 224658.3, 224725.7, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0301 \n",
      "   targetWP, latest drx4 are tWP,dr, 224897.1,0.9104, 224897.1,0.0264, 224897.1,0.0003, 224897.1,0.0008\n",
      "loop32.0, tr8891,wedgePops879218.19, 85659.1, 344175.0, 224658.3, 224725.7, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0301 \n",
      "   targetWP, latest drx4 are tWP,dr, 224897.1,0.9104, 224897.1,0.9104, 224897.1,0.0003, 224897.1,0.0008\n",
      "loop33.0, tr8891,wedgePops870889.28, 85659.1, 335846.1, 224658.3, 224725.7, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0401 \n",
      "   targetWP, latest drx4 are tWP,dr, 224897.1,0.9104, 224897.1,-0.6769, 224897.1,0.0003, 224897.1,0.0008\n",
      "loop34.0, tr8891,wedgePops661853.66, 85659.1, 126810.5, 224658.3, 224725.7, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0401 \n",
      "   targetWP, latest drx4 are tWP,dr, 224897.1,0.9104, 224897.1,-0.7117, 224897.1,0.0003, 224897.1,0.0008\n",
      "loop35.0, tr8891,wedgePops753291.89, 85659.1, 218248.7, 224658.3, 224725.7, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0501 \n",
      "   targetWP, latest drx4 are tWP,dr, 224897.1,0.9104, 224897.1,0.3141, 224897.1,0.0003, 224897.1,0.0008\n",
      "loop36.0, tr8891,wedgePops753291.89, 85659.1, 218248.7, 224658.3, 224725.7, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0501 \n",
      "   targetWP, latest drx4 are tWP,dr, 224897.1,0.9104, 224897.1,0.0153, 224897.1,0.0003, 224897.1,0.0008\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 36.0 1 43.0 1.0411 218248.7\n",
      "loop37.0, tr8891,wedgePops753291.89, 85659.1, 218248.7, 224658.3, 224725.7, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0501 \n",
      "   targetWP, latest drx4 are tWP,dr, 224897.1,0.9104, 224897.1,0.0236, 224897.1,0.0003, 224897.1,0.0008\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 37.0 1 43.0 1.0647 218248.7\n",
      "loop38.0, tr8891,wedgePops753291.89, 85659.1, 218248.7, 224658.3, 224725.7, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0501 \n",
      "   targetWP, latest drx4 are tWP,dr, 224897.1,0.9104, 224897.1,0.0241, 224897.1,0.0003, 224897.1,0.0008\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 38.0 1 43.0 1.0889 218248.7\n",
      "loop39.0, tr8891,wedgePops753291.89, 85659.1, 218248.7, 224658.3, 224725.7, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0501 \n",
      "   targetWP, latest drx4 are tWP,dr, 224897.1,0.9104, 224897.1,0.0247, 224897.1,0.0003, 224897.1,0.0008\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 0 4.30131 85589.9149 85659.1494 1\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 1 1.11355 218248.7323 218248.7323 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 2 0.12352 223690.0439 224658.2548 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 3 0.25714 224009.2712 224725.7491 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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FZBdQEbhoc0ZjzBJjTIQxJiIkJMRFsb2XXRoT33rDHayc+waHjx6iZ2wbTp85ZUkOpdTlK9KFPMaYdGA70MwYs88Y08QYUxd4GfjJ9fGKp7tr38uiGev45oevLG1MXP+uB1k49SV27/2C/mO6cT7rvCU5lFKXpzDvQgkRkQDn1+WAxsA+EQl1LvMBngYWuzFnsdPkH5HEjXne8sbEzRu1ZdrIBWz76C1GTntSr9ZUyosU5n3gVYBVIuJLbsF/1RizRUSGiMhA53PeAFa6K2Rxlb8xcagjnPFDnrUkR48O0SSnJjB36VRCg8MYM2iaJTmUUkVTYAE3xuwB7rzI8vnAfHeEKkkG9x5Ncmoii1fPJSQ4jP5RsZbkGBY9nsSUBBa+OItQRxX6dBlkSQ6lVOHplZgWExEmD59Dcloizzw3ipCgUNo372ZJjhmj40lLT2binOE4AkNo3bSzx3MopQpPP43QBvIaE98X0ZBhk59g+yfvWpZj4dTV1KtzP0Mm9uaDz7ZZkkMpVThawG0if2PiJ0Z2ZvfenZbkKFumLCvnvsH1NW6i74iOfLPvK0tyKKUKpgXcRvI3Ju4+pJVljYkrVwxgTfwWAioFETW4JYd+03eIKmVHWsBtxi6NicNDrmLdwi1kZ2fTdWALklMTLcmhlLo0LeA2lL8xcdTglpY1Jr6+xs28NH8jSakJRA1uycmME5bkUEpdnBZwm8prTPzjT9/Re3gHyxoT33VbPZbEvcL3B76h78hOZJ7LtCSHUuqvtIDb2B+NiXftsLQxcaP7mzFn/BI++vx9hk7sbdlVo0qpP9MCbnP5GxOPnx1r2aXuHSO7My5mOpveW8+kuU/pJfdK2YBeyOMF/tSYODicoX3HWpLjyR7DSUxJYNnLCwh1hDPo8ZGW5FBK5dIC7iXyGhPPWjyJkOAwSxoTiwgTY2eSkpbIjIVPExIURudWPT2eQymVSwu4l7iwMbEjMISmDVsVvKIbcsybtJy09FRGTOtPUKCDRx5s4fEcSimdA/cq+RsTDxgXZVlj4tKlSrN05r+odWNt+o/uys49n1qSQ6mSTgu4l7FLY2L/ChVZPX8T4aFV6Rnbhv0Hv7ckh1IlmRZwL2SXxsSOoFDWxW+hlF8pug6K5Gjib5bkUKqk0gLupezSmPiaatexZv4mTmSkExUTSfqJ45bkUKokKkxLtbIi8rmIfC0ie0VksnN5HRH5VER2O7vO13N/XJWfXRoT33bznSyf/RoHDx+g17B2nDl7xpIcSpU0hXkFngk0MsbUBuoAzUSkPjATmOzsVj/B+b3yMLs0Jn7g7oeYP2UlX3z9MQPHRZGVlWVJDqVKkgILuMmV4fy2lPNmnLdKzuWVgaNuSagK1LxRW6aPimfbR28xatoAy66SbPVIR6YMn8s7OzYzNi5Gr9ZUys0K9T5wZ0PjXcD1wD+NMZ+JyFDgHRGZTe4vgvsusW40EA1QvXp1V2RWF9G9/RMkpRxj7tKphDjCGDNwqiU5encZSFJqAvEr4wgJDmNE/0mW5FD2duZsNilp5wkKKEWF8r5Wx/FahSrgxphsoI6IBAAbROQ2cotyrDHmdRHpBCwHGl9k3SXAEoCIiAh9SeZGw6LHk5SayMKVMwkNDresMfGoAVNITk3kuWXTCXVUoWeHfpbkUO5xNjOHIwmZHEnI5Kjz/jfn/ZFjuffnswr3o/5Avcr86/nb3Jy4+CrSlZjGmHQR2Q40A3oCQ5wPrQeWuTaaKioRYfqoBaQeT8ptTBwUSusmnSzJETf2eVKOJzEubjDBAQ4iG7f3eA7leod+O8P9bb684u34+EBODvTqVMUFqUquAgu4iIQA553Fuxy5r7LjyJ3zbgBsBxoB+92YUxVSXmPiroOaM2RCLwIrB/OPex72eA4/Pz8Wz1hH5wHNiBnfk6AAB/dFNPB4DuVaVcPL0O7REL7ae5Kq4WWoGlYm9z68DFfl3YeVplxZnRbxBCnoRJOI3AGsAnzJnet+1RgzRUQeAOaT+0vgLDDAGLPr77YVERFhdu60pllvSfP7yXTaP9GIX48e4vUl27j95jstyXH89zTa9m1IQtJRXl+6jVo31rYkh7KPiXPe45brQ+nSWv8vFJaI7DLGRPxluSffKaAF3LMSko/Sqtc/yDx3lo0rdlCjWk1LchxJOEzrPg3Izspi44odVK96rSU5lD1UjZgOwMgnGzCkz/0Wp/EOlyrgeiVmMWaXxsRVw69m7YLNZJ47S9eYFqQeT7Ykh7KHD17PPak9c9EONry91+I03k0LeDGXvzFx9yGtyDh10pIcN9Wsxap5b3Is8Td6DGnNqdMZBa+kiqWa1wSzYVl3AAY9vZFPv7Tms3yKAy3gJUBeY+Lv9u+hz4iOljUmvrvOfSyavpY9+74kelQXzp0/Z0kOZb16da7m+WmtAWgfvYYDh6z5LB9vpwW8hLBLY+ImDVoyc+witn/yLsOnRGuD5BKsddNajBqQ+86kBh1eIDlV/yorKi3gJcifGhPPG2HZpe6PtenFyCcn88a/1zEt3pr+nsoeBve+nw4tbgegTtMFFqfxPtpSrYTJ35g4LDicgY+PsCTH4N6jSUpJYPHquYQEh9E/KtaSHMp6cye0IP3EGbq1teatrt5MC3gJk78x8fSF43AEh9G5ZQ9Lckx5ai4px5N45rlRhASF0r55N4/nUNbz9fVh1TzPXzFcHGgBL4H+1Jh4aj+CAx00fqC5x3P4+vqyYMqLpKWnMmzyEwQHhtDw3iYez6GUt9I58BIqf2PifqMes6wxcZnSZVg+ez031ryVJ0Z2ZvdevdBLqcLSAl6C2aUxcSX/yqxZsBlHUCjdh7Tip19+tCSHUt5GC3gJZ5fGxGGOKqyN34KI0C0mksSUY5bkUMqbaAFXtmlMfF31G1g9fxOpx5OJGtySExm/W5JDKW+hBVwB9mlMXPvWuiyb9So//vQdvYd34GzmWUtyKOUNtICrP+RvTDzo6e6WNSZuUP8R5k1axie7dhAzvifZ2dmW5FDK7rSAqz/Ja0z89vZNljYmbvdoVybGzuKt9zcwfnasNkhW6iL0feDqL/I3Jg51hPNUv4mW5IjuNoSklGMsWj2X0OBwhvbVy+6Vyk8LuLqovMbE85ZOIyQ43LLGxGNjppOclsSsxZMICQ6jW9s+luRQyo4K0xOzLPABUMb5/NeMMRNF5F/ATc6nBQDpxpg6bsqpPCyvMXHq8WTGxQ3GERhCi4fbeTyHj48Ps8e/QNrxFEbPGIgjMISmDVt5PIdSdlSYOfBMoJExpjZQB2gmIvWNMZ2NMXWcRft14A33xVRW8PPzY9GMtdx1+z0MeroHH+/cYUmOUn6leCHuZWrfUpcB46L4fPf/LMmhlN0UWMBNrrwP6i3lvP1xRklEBOgEvOyWhMpS5cqWZ9W8N7mm2nX0Ht6evT9+bUmO8uUq8NL8jVQNr87jsW3Zd+BbS3IoZSeFeheKiPiKyG4gCXjPGPNZvocfBBKNMfsvsW60iOwUkZ3JydoL0RsFVg5ibfxW/P0rERXTkl+PHLQkR1CAg3ULt1K2TDm6DW7JkQRtxaVKtkIVcGNMtnOqpBpQT0Ruy/fwY/zNq29jzBJjTIQxJiIkJOSKwirr2KUxcbUq17AmfjOnT2fQdVAL0tK1FZcquYr0PnBjTDqwHWgGICJ+QDvgX64OpuzHLo2Jb73hDlbMeZ3DRw/RM7YNZ86etiSHUlYrsICLSIiIBDi/Lgc0BvY5H24M7DPGWPMJSMrjLmxMfD7rvCU57q37DxZOfYnde7+g3+iuluVQykpS0BVuInIHsArwJbfgv2qMmeJ87EXgU2PM4sLsLCIiwuzcqZ/3XBy8/OZKnpraj3aPdmX+5BX4+FhzUe9Lry1hzLOD6NyyJ3MmLCH3nLpSrmOM4fSZs5zIOMXJjFN/uc/7+sTJUySlpnE0IZkjiUkkp/7/h8I91roZM8cNveyfExHZZYyJuHB5ge8DN8bsAS7arM4Y8/hlpVFe77E2vUhKTWDmoomEOsIZP+RZS3L06BBNcmoCc5dOJcQRxpiBUy3JoeypsMX3ZMZpktOOc+RYIr8l/Ln4usLLG9+mX1QHbri2uku3q1diqstml8bEw6LHk5iSwMKVMwkNDqdPl0GW5FCuZYzhzNmznMg4ne9Vbsali29CEkcTkkhMSfNIvoDKFakaFkrV8FDCQoKpXLECFf1zb5X9/anoX4FK/hWo6F+e4MAAQoIDXZ5BC7i6bHZpTCwizBgdT1p6MhPnDMcRFErrJtok10oXK76XmnawpPhWqshV4SFUCw/7S/GtdJH7Sv4VqFC+nGVThZeiBVxdEbs0Jvb19WXh1NV0HdScIRN6EVg5mH/c87DHcxRnE+YswuTkUDU89I9CnJyWzpGEJI4cS/RY8a1c0Z+qVUKpGpb3ytefiv7lc1/5VvS/aBH2t2HxdYUCT2K6kp7ELL5OZPxOh+jGHDx8gPWL36NOrb+cb/GI30+m067vQxw+9guvL9nG7Tdf9PSNKqLzWVnUqN/8irdTyb8CVcNDuSo8lCqhjj8V34u98s0rvr6+vi4Yhfe61ElMLeDKZZJSEmjdpwEZp07y5vLt1LzmRktyHEs6QuveDcg8d5aNK3ZQo1pNS3IUJ+ezsmgf/RSHDh+hTq2bCf/jle//z/NWquivxddNtIArj/j51/206dOQ8uUqsHHFDsIcVSzJceDQPtr0eYjKFQN4c/l2QoLDLMmhlCtcqoAXv0khZSm7NCa+vsbNvDR/I4kpx+g+pBUZp05akkMpd9ICrlzOLo2J77qtHkviXuG7/XvoM6IjmecyLcmhlLtoAVdukb8x8eAJj1vWmLjR/c2YPf4FPvr8fYZO7E1OTo4lOZRyBy3gym3yGhNv3faGpY2JO0X2YFzMdDa9t55J80Zog2RVbOj7wJVb2aUx8ZM9hpOYksCylxcQFhzOwMdHWJJDKVfSAq7czg6NiUWEibEzSUlLZPrCcTiCw+jcsofHcyjlSlrAldvZpTGxj48P8yYtJy09lRFT+xEc6KDxA1d+cYpSVtE5cOURdmlMXLpUaZbO/Be1bqxNv1GPseubzwpeSSmb0gKuPMYujYn9K1Rk9fxNhIdWpcfQ1uw/+L0lOZS6UlrAlUfZpTGxIyiUdfFbKOVXiq6DIjmaqE2llPcpTEu1siLyuYh8LSJ7RWRyvsdiROQH5/KZ7o2qiov8jYm7xURa1pj4mmrXsWb+Jk5kpBMVE0n6Cdd+iL9S7laYV+CZQCNjTG2gDtBMROqLyENAa+AOY0wtYLb7YqriJq8x8a9HDlramPi2m+9k+ezXOHj4AL2GtePM2TOW5FDqchRYwE2uvPbjpZw3AzwJPGuMyXQ+L8ltKVWxZJfGxA/c/RDzp6zki68/ZtDT3cnKyrIkh1JFVag5cBHxFZHdQBLwnjHmM+BG4EER+UxEdojI3ZdYN1pEdorIzuTkZJcFV8VD80ZtmTZyAds+eotR0wZYdpVkq0c6MmX4XN7evomxcTF6tabyCoV6H7gxJhuoIyIBwAYRuc25biBQH7gbeFVErjMX/M83xiwBlkDux8m6MLsqJuzSmLh3l4EkpSYQvzKOUEc4T/WbaEkOpQqrSBfyGGPSRWQ70Az4DXjDWbA/F5EcwAHoy2xVZHZpTDxqwBSSUxOZt3QaIcHh9OzQz5IcShVGgQVcREKA887iXQ5oDMQBGUAjYLuI3AiUBlLcGVYVX3ZpTCwixI19npTjSYyLG4wjMIQWD7fzeA6lCqMwc+BVgP+KyB7gC3LnwLcAK4DrRORb4BWg54XTJ0oVRV5j4np17mfIhF588Nk2S3L4+fmxeMY67rr9HgY93YOPd+6wJIdSBdGWasp27NKY+PjvabTt25CEpKO8vnQbtW6sbUkOpbSlmvIalSsGsCZ+CwGVgoga3JJDv/1kSY7AykGsjd+Kv38lomJacvjoIUtyKHUpWsCVLVUJrcq6hVvIzs6m26BIklMTLclRNfxq1i7YTOa5s3Qd1ILU43qOXtmHFnBlW3ZpTHxTzVqsmvcmRxMP02NIa06dzih4JaU8QAu4srX8jYn7jujEufPnLMlxd537WDR9LXv2fUn0qC6WXTWqVH5awJXt5TUm/vDzbZY2Jm7SoCVxY59n+yfvMmzyE9ogWVlOO/Ior9ApsgcpqUlMix+LIziMycNmIyIez9G1TW+SUxOZuWgioY5wxg951uMZlMqjBVx5Dbs0Jh7cezRJKQksXj2XkOAw+kfFWpJDKS3gymvYpTGxiDDlqbmkHE/imedGERIUSvvm3TyeQykt4Mqr5DUmTj2eYmljYl9fXxZMeZG09FSGTX6C4MAQGt7bxOM5VMmmJzGV1yldqjTLZr1qeWPiMqXLsHz2em6seStPjOzM7r16lbHyLC3gyivZpTFxJf/KrFmwGUdQKN2HtOKnX360JIcqmbSAK691YWPiY0lHLMkR5qjC2vgtiAjdYiJJTDlmSQ5V8mgBV17NLo2Jr6t+A6vnbyL1eDJRg1tyIuN3S3KokkULuPJ6eY2Jf/51v6WNiWvfWpdls17lx5++o/fwDpzNPGtJDlVyaAFXxYJdGhM3qP8I8yYt45NdOxg84XGys7MtyaFKBi3gqtiwS2Pido92ZWLsLLZue4Pxs2O1QbJym8K0VCsLfACUcT7/NWPMRBGZBDzB//fAHGuMectdQZUqDLs0Jo7uNoSklGMsWj2X0OBwhvYda0kOVbwV5kKeTKCRMSZDREoBH4nIv52PzTPGzHZfPKWKzi6NicfGTCcpNZFZiycR6gina5veluRQxVeBBdzZ5zLvA5BLOW/6N6GyLbs0Jvbx8WHOhCUcT09l1PQBBAc4aNqwlcdzqOKrUHPgIuIrIruBJHKbGudd+jZIRPaIyAoRCbzEutEislNEdiYnazcT5Rl2aUxcyq8UL8S9TO1b6jJgXBRf7P7YkhyqeCpSU2MRCQA2ADHkzn2nkPtq/BmgijHmb/9G1KbGytPs0pg4LT2F1r0bkHo8mQ3L/stNNWtZkkN5J5c0NTbGpAPbgWbGmERjTLYxJgdYCtRzRVClXMkujYmDAhysW7iVsmXK0TUmkiMJv1qSQxUvBRZwEQlxvvJGRMoBjYF9IlIl39PaAt+6JaFSV8gujYmvvqoGa+I3c/p0Bt1iIklLT7Ukhyo+CvMKvArwXxHZA3xB7hz4FmCmiHzjXP4QoJ9qr2zLLo2Jb73hDlbMeZ1fjxykZ2wbzpw9bUkOVTwUaQ78SukcuLLauzs202dER/5xT2NenLeBUn6lLMnx1vsb6Df6MRrd34zls17Dz08/ml9dmkvmwJXydnZpTNy8UVumjVzAfz58i5HTntSrNdVl0V/7qsSxS2PiHh2iSU5NYO7SqYQ4whgzcKolOZT30gKuSiS7NCYeFj2exJQEFq6cSVhwFXp3GWhJDuWdtICrEimvMXFyWqKljYlFhBmj40lLT2bCnGEEB4XQukknj+dQ3knnwFWJ5evrS/wzq7gvoiHDJj/B9k/etSzHwqmrqVfnfoZM6MWHn79vSQ7lfbSAqxLNLo2Jy5Ypy8q5b1DzmhvpO6Ij3+z7ypIcyrtoAVclnl0aE1euGMCa+C1UrhhI1OCWHPrtJ0tyKO+hBVwp7NOYuEpoVdYt3EJ2djbdBkWSnJpoSQ7lHbSAK+Vkl8bE19e4mVXPvUlC8lG6D2lFxqmTluRQ9qcFXKl87NKYuO7t97Ak7hW+27+HviM6ce78OUtyKHvTAq7UBezSmPjhBx5l9vgX+PDzbYyaPsCSDMretIArdRHtHu3KhKEzLW9MHPlwexxBoew/uM+S/St70wt5lLqEflFDSU5NsLQx8T9XzSIlLYklca94fN/K/rSAK/U3rGxM/OuRgyx6aQ5tmnbmnjsf8Nh+lffQAq7U37CyMfEzz43Cx8eXcYNneGR/yvvoHLhSBbCiMfEHn23jrf++SUyvUVwVVs3t+1PeSQu4UoVQvlwFXpq/kavCrqZnbBt++Gmv2/Z1Pus8E+cMo3rVa+ln0ackKu9QmJ6YZUXkcxH5WkT2isjkCx5/SkSMiDjcF1Mp63mqMfGq9Yv58efvmRQ7i7JlyrplH6p4KMwr8EygkTGmNlAHaCYi9QFE5GrgEUBbbKsSwd2NiVPSkpjzwhQa1H+EJg1aunTbqvgpsICbXHkdYEs5b3lvip0HjMz3vVLFnjsbE8c9P4HTZ04xefhsRMRl21XFU6HmwEXEV0R2A0nkdqX/TERaAUeMMV8XsG60iOwUkZ3JyclXnlgpG7i37j9YOPUlvvr2c/qP6UpWVtYVb3PP91/y8saV9O4yiBuuvcUFKVVxV6gCbozJNsbUAaoB9UTkDmAcMKEQ6y4xxkQYYyJCQkKuKKxSdtK8UVumj4p3SWNiYwxPzxpKcGAIsU+Mc2FKVZwV6X3gxph0EdkOtAauBb52/plXDfhSROoZYxJcnlIpm3JVY+I3/r2OXXs+Zc74JVTyr+zilKq4KrCAi0gIcN5ZvMsBjYE4Y0xovuccAiKMMSluS6qUTeVvTBwaHE6fLoOKtH7GqZNMWzCW2rfWpVPLHm5KqYqjwrwCrwKsEhFfcqdcXjXGbHFvLKW8R15j4tTjSUycMxxHUGiRGhMvWDGDxJRjLJ31Kj4+emmGKrwCC7gxZg9wZwHPqeGqQEp5o7zGxN1iWjBkQi+CAhw8WK9Rgev9/Ot+lqydT8fI7tS9/R4PJFXFif66V8pFypUtV+TGxJPmjqBMmbKMGXR5c+eqZNMCrpQLFaUx8baP/s22j94itu84whxVPJhSFRdawJVyscI0Jj53/hwT5w7nuuo30LuIJz2VyqMFXCk3KKgx8fKX4zn46wGmPDWX0qVKW5RSeTst4Eq5yaUaEyemHGPesmk0frA5D93X1OKUyptpAVfKjfI3Jh46sTc5OTlMjx/H+fPnmDRsttXxlJfTjjxKuVmnyB4kpyQyfeE4zpw9zbsfbGHQ4yO49urrrY6mvJwWcKU8YEDPp0hKTWTZywsID7mKwb3HWB1JFQNawJXyABFhYuxMggMd1KtzPxXK+1sdSRUDWsCV8hAfHx8G9x5tdQxVjOhJTKWU8lJawJVSyktpAVdKKS+lBVwppbyUFnCllPJSWsCVUspLaQFXSikvpQVcKaW8lBhjPLczkWTgl0s87AC8vSlycRgD6DjspDiMAYrHOKwcwzXGmJALF3q0gP8dEdlpjImwOseVKA5jAB2HnRSHMUDxGIcdx6BTKEop5aW0gCullJeyUwFfYnUAFygOYwAdh50UhzFA8RiH7cZgmzlwpZRSRWOnV+BKKaWKQAu4Ukp5KbcWcBHpKCJ7RSRHRCLyLX9ERHaJyDfO+0b5HtsuIj+IyG7nLfQS2x4jIgecz3Vra+/LGUe+52wSkW8vsd0aInIm31gXe9sYnI/b+liIyNsi8rVzvcUi4nuR7XrsWLhzHM7neeR4FHUMIlJeRLaKyD7nes9eYru2PhaFHYfzue49FsYYt92AW4CbgO1ARL7ldwJXOb++DTiS77E/PfcS270V+BooA1wL/AT42mkczmXtgHXAt5fYbo1LPeZFY7D9sQAqOe8FeB3oYuWxcPM4PHY8ijoGoDzwkPPr0sCHwKPediyKMA63Hwu3tlQzxnwPuf0AL1j+Vb5v9wJlRaSMMSazkJtuDbzifP5BETkA1AM+ufLUf3U54xARf2AYEA286o5cReHGMdj+WBhjTjiX+5H7A2f5mXs3jsNjx+MyxnAa+K/zOedE5EugmqtzFZUbx+H2Y2GHOfD2wFcXFO+Vzj+dxsuF/6q5qgKH833/m3OZlS4cxzPAHOB0AetdKyJficgOEXnQrQkLdjlj8IZjgYi8AyQBJ4HXLrGenY4FXN447HY8LvbzjYgEAC2BbZdYz/bHAgoch9uPxRW/AheR/wDhF3lonDFmYwHr1gLigCb5FnczxhwRkYrk/pnYHXjpwlUvsrkrelXlynGISB3gemNMrIjU+JtVjwHVjTGpIlIXeFNEauV7peUNY7D1sfgjkDFNRaQssBZoBLx3waouPRYWjsOlx8MdYxARP+BlYIEx5ueLrOoVx6IQ43D5z8aFrriAG2MaX856IlIN2AD0MMb8lG97R5z3J0VkHbl/clxYwH8Drs73fTXg6OXkyLdfV47jXqCuiBwi9984VES2G2MaXrDPTCDT+fUuEfkJuBHY6S1jwP7HIv92z4rIJnL/tH3vgsdceiyc2/H4OHDx8XDTGJYA+40xz11in95yLP52HLjhZ+MvXDmhfqkbfz05EEDu5H77C57nBzicX5ci90/E/hfZXi3+fHLgZ9x44qyo47hgnRpc+gRgSF5u4DrgCBDkZWOw9bEA/IEq+f5//QsYZIdj4aZxePx4FOX/FDCV3L+sff5me7Y+FkUYh9uPhbv/QdqS+1soE0gE3nEufxo4BezOdwsFKgC7gD3knjSYn+9AtgKm5Nv2OHLP6v7ARc4AWzmOC9atQb7il38c5M6r7XUe5C+Blt42BrsfCyAM+CLf/6l4wM/KY+HOcXjyeFzGGKqRO4Xwfb7lfb3wWBRqHJ44FnopvVJKeSk7vAtFKaXUZdACrpRSXkoLuFJKeSkt4Eop5aW0gCullJfSAq6UUl5KC7hSSnmp/wPDi4MIt1ldtgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8891 39.0 1 43.0 1.1136 218248.7\n",
      "loop40.0, tr8891,wedgePops753291.89, 85659.1, 218248.7, 224658.3, 224725.7, Overedge?1, 0, 0, 0, ,Satisfied?0011,yoyo?0501 \n",
      "   targetWP, latest drx4 are tWP,dr, 224897.1,0.9104, 224897.1,0.0253, 224897.1,0.0003, 224897.1,0.0008\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 0 4.30131 85589.9149 85659.1494 1\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 1 1.1388 218248.7323 218248.7323 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 2 0.12352 223690.0439 224658.2548 0\n",
      "wedge no, currentR,oldWedgePop, wedgePop, overEdge? 3 0.25714 224009.2712 224725.7491 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I looped 40 times on tract 8891, giving up w pop 753291.8856496646\n",
      "I am working on tract number 8900 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8904 4.0 1 90.0 1.4173 199750.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8904 12.0 1 90.0 1.4757 199750.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8904 13.0 1 90.0 1.4215 199750.5\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8904 1 196407.47194225018 1.1723\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8904 1 118635.29737883905 0.5861\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8904 1 199723.5678632487 1.3584\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8904 1 144996.51721826516 0.9723\n",
      "11 yoyos for tract,wedge,wedgePop,r= 8904 1 196280.57129158505 1.1653\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8904 1 153670.1151559358 1.0688\n",
      "12 yoyos for tract,wedge,wedgePop,r= 8904 1 181951.36844409775 1.1171\n",
      "13 yoyos for tract,wedge,wedgePop,r= 8904 1 195867.54153799842 1.1412\n",
      "13 yoyos for tract,wedge,wedgePop,r= 8904 1 193379.02399731657 1.1291\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8916 8.0 3 61.4 0.3367 150198.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8916 9.0 3 61.4 0.3998 150198.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8916 10.0 0 118.6 0.3993 187655.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8916 10.0 3 61.4 0.4747 150198.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8916 11.0 0 118.6 0.4032 187655.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8916 11.0 3 61.4 0.5637 150198.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8916 12.0 0 118.6 0.4071 187655.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8916 12.0 3 61.4 0.6694 150198.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8916 13.0 0 118.6 0.411 187655.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8916 14.0 0 118.6 0.415 187655.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8916 15.0 0 118.6 0.419 187655.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8916 16.0 0 118.6 0.4231 187655.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8916 17.0 0 118.6 0.4272 187655.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8917 7.0 3 54.8 0.7921 108636.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8918 4.0 2 250.9 0.2039 70330.8\n",
      "I am working on tract number 8920 of 9129 tracts\n",
      "need to widen edge circle beyond 0.0010163358241416902 for tract (x,y)=( -122.30460720868497 37.52721050172667\n",
      "need to widen edge circle beyond 0.0011179694065558592 for tract (x,y)=( -122.30460720868497 37.52721050172667\n",
      "need to widen edge circle beyond 0.0012297663472114451 for tract (x,y)=( -122.30460720868497 37.52721050172667\n",
      "need to widen edge circle beyond 0.0013527429819325898 for tract (x,y)=( -122.30460720868497 37.52721050172667\n",
      "need to widen edge circle beyond 0.0014880172801258488 for tract (x,y)=( -122.30460720868497 37.52721050172667\n",
      "need to widen edge circle beyond 0.0016368190081384338 for tract (x,y)=( -122.30460720868497 37.52721050172667\n",
      "need to widen edge circle beyond 0.0018005009089522774 for tract (x,y)=( -122.30460720868497 37.52721050172667\n",
      "need to widen edge circle beyond 0.0019805509998475053 for tract (x,y)=( -122.30460720868497 37.52721050172667\n",
      "need to widen edge circle beyond 0.002178606099832256 for tract (x,y)=( -122.30460720868497 37.52721050172667\n",
      "need to widen edge circle beyond 0.002396466709815482 for tract (x,y)=( -122.30460720868497 37.52721050172667\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "need to widen edge circle beyond 0.0007074980333848191 for tract (x,y)=( -122.29749094579294 37.53317007114076\n",
      "need to widen edge circle beyond 0.000778247836723301 for tract (x,y)=( -122.29749094579294 37.53317007114076\n",
      "need to widen edge circle beyond 0.0008560726203956312 for tract (x,y)=( -122.29749094579294 37.53317007114076\n",
      "need to widen edge circle beyond 0.0009416798824351944 for tract (x,y)=( -122.29749094579294 37.53317007114076\n",
      "need to widen edge circle beyond 0.001035847870678714 for tract (x,y)=( -122.29749094579294 37.53317007114076\n",
      "need to widen edge circle beyond 0.0011394326577465854 for tract (x,y)=( -122.29749094579294 37.53317007114076\n",
      "need to widen edge circle beyond 0.001253375923521244 for tract (x,y)=( -122.29749094579294 37.53317007114076\n",
      "need to widen edge circle beyond 0.0013787135158733685 for tract (x,y)=( -122.29749094579294 37.53317007114076\n",
      "need to widen edge circle beyond 0.0015165848674607056 for tract (x,y)=( -122.29749094579294 37.53317007114076\n",
      "need to widen edge circle beyond 0.0016682433542067763 for tract (x,y)=( -122.29749094579294 37.53317007114076\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "7 yoyos for tract,wedge,wedgePop,r= 8932 1 264494.3071744325 1.7251\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8932 1 2110578.077873989 3.6979\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8932 1 622838.6101810248 2.7115\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8932 1 447677.56236389896 2.2183\n",
      "8 yoyos for tract,wedge,wedgePop,r= 8932 1 437709.21526469185 1.9717\n",
      "9 yoyos for tract,wedge,wedgePop,r= 8932 1 336666.2448595654 1.8484\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8932 1 421726.67135885113 1.9101\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8932 1 392515.5392925295 1.8792\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8932 1 372337.28226609045 1.8638\n",
      "10 yoyos for tract,wedge,wedgePop,r= 8932 1 356333.104202573 1.8561\n",
      "need to widen edge circle beyond 0.0008556953985864446 for tract (x,y)=( -122.29973569122961 37.546732237802445\n",
      "need to widen edge circle beyond 0.0009412649384450891 for tract (x,y)=( -122.29973569122961 37.546732237802445\n",
      "need to widen edge circle beyond 0.001035391432289598 for tract (x,y)=( -122.29973569122961 37.546732237802445\n",
      "need to widen edge circle beyond 0.001138930575518558 for tract (x,y)=( -122.29973569122961 37.546732237802445\n",
      "need to widen edge circle beyond 0.001252823633070414 for tract (x,y)=( -122.29973569122961 37.546732237802445\n",
      "need to widen edge circle beyond 0.0013781059963774555 for tract (x,y)=( -122.29973569122961 37.546732237802445\n",
      "need to widen edge circle beyond 0.0015159165960152011 for tract (x,y)=( -122.29973569122961 37.546732237802445\n",
      "need to widen edge circle beyond 0.0016675082556167214 for tract (x,y)=( -122.29973569122961 37.546732237802445\n",
      "need to widen edge circle beyond 0.0018342590811783936 for tract (x,y)=( -122.29973569122961 37.546732237802445\n",
      "need to widen edge circle beyond 0.002017684989296233 for tract (x,y)=( -122.29973569122961 37.546732237802445\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "I am working on tract number 8940 of 9129 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 8946\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8951 5.0 3 53.3 0.208 55276.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8953 5.0 3 45.0 0.168 57481.7\n",
      "need to widen edge circle beyond 0.0008719506317409494 for tract (x,y)=( -122.30339061029487 37.5711423990003\n",
      "need to widen edge circle beyond 0.0009591456949150445 for tract (x,y)=( -122.30339061029487 37.5711423990003\n",
      "need to widen edge circle beyond 0.001055060264406549 for tract (x,y)=( -122.30339061029487 37.5711423990003\n",
      "need to widen edge circle beyond 0.001160566290847204 for tract (x,y)=( -122.30339061029487 37.5711423990003\n",
      "need to widen edge circle beyond 0.0012766229199319245 for tract (x,y)=( -122.30339061029487 37.5711423990003\n",
      "need to widen edge circle beyond 0.0014042852119251171 for tract (x,y)=( -122.30339061029487 37.5711423990003\n",
      "need to widen edge circle beyond 0.001544713733117629 for tract (x,y)=( -122.30339061029487 37.5711423990003\n",
      "need to widen edge circle beyond 0.001699185106429392 for tract (x,y)=( -122.30339061029487 37.5711423990003\n",
      "need to widen edge circle beyond 0.0018691036170723314 for tract (x,y)=( -122.30339061029487 37.5711423990003\n",
      "need to widen edge circle beyond 0.0020560139787795645 for tract (x,y)=( -122.30339061029487 37.5711423990003\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "need to widen edge circle beyond 0.0009061570616067898 for tract (x,y)=( -122.29487874649747 37.560794633417906\n",
      "need to widen edge circle beyond 0.000996772767767469 for tract (x,y)=( -122.29487874649747 37.560794633417906\n",
      "need to widen edge circle beyond 0.0010964500445442159 for tract (x,y)=( -122.29487874649747 37.560794633417906\n",
      "need to widen edge circle beyond 0.0012060950489986375 for tract (x,y)=( -122.29487874649747 37.560794633417906\n",
      "need to widen edge circle beyond 0.0013267045538985014 for tract (x,y)=( -122.29487874649747 37.560794633417906\n",
      "need to widen edge circle beyond 0.0014593750092883517 for tract (x,y)=( -122.29487874649747 37.560794633417906\n",
      "need to widen edge circle beyond 0.001605312510217187 for tract (x,y)=( -122.29487874649747 37.560794633417906\n",
      "need to widen edge circle beyond 0.001765843761238906 for tract (x,y)=( -122.29487874649747 37.560794633417906\n",
      "need to widen edge circle beyond 0.0019424281373627967 for tract (x,y)=( -122.29487874649747 37.560794633417906\n",
      "need to widen edge circle beyond 0.0021366709510990765 for tract (x,y)=( -122.29487874649747 37.560794633417906\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "I am working on tract number 8960 of 9129 tracts\n",
      "need to widen edge circle beyond 0.001068861064867361 for tract (x,y)=( -122.28641930120348 37.5614035641054\n",
      "need to widen edge circle beyond 0.0011757471713540971 for tract (x,y)=( -122.28641930120348 37.5614035641054\n",
      "need to widen edge circle beyond 0.0012933218884895068 for tract (x,y)=( -122.28641930120348 37.5614035641054\n",
      "need to widen edge circle beyond 0.0014226540773384577 for tract (x,y)=( -122.28641930120348 37.5614035641054\n",
      "need to widen edge circle beyond 0.0015649194850723036 for tract (x,y)=( -122.28641930120348 37.5614035641054\n",
      "need to widen edge circle beyond 0.0017214114335795342 for tract (x,y)=( -122.28641930120348 37.5614035641054\n",
      "need to widen edge circle beyond 0.0018935525769374878 for tract (x,y)=( -122.28641930120348 37.5614035641054\n",
      "need to widen edge circle beyond 0.0020829078346312367 for tract (x,y)=( -122.28641930120348 37.5614035641054\n",
      "need to widen edge circle beyond 0.0022911986180943603 for tract (x,y)=( -122.28641930120348 37.5614035641054\n",
      "need to widen edge circle beyond 0.0025203184799037965 for tract (x,y)=( -122.28641930120348 37.5614035641054\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "need to widen edge circle beyond 0.0008738261935804961 for tract (x,y)=( -122.26724536122664 37.54886792560715\n",
      "need to widen edge circle beyond 0.0009612088129385458 for tract (x,y)=( -122.26724536122664 37.54886792560715\n",
      "need to widen edge circle beyond 0.0010573296942324004 for tract (x,y)=( -122.26724536122664 37.54886792560715\n",
      "need to widen edge circle beyond 0.0011630626636556405 for tract (x,y)=( -122.26724536122664 37.54886792560715\n",
      "need to widen edge circle beyond 0.0012793689300212047 for tract (x,y)=( -122.26724536122664 37.54886792560715\n",
      "need to widen edge circle beyond 0.0014073058230233252 for tract (x,y)=( -122.26724536122664 37.54886792560715\n",
      "need to widen edge circle beyond 0.0015480364053256578 for tract (x,y)=( -122.26724536122664 37.54886792560715\n",
      "need to widen edge circle beyond 0.0017028400458582239 for tract (x,y)=( -122.26724536122664 37.54886792560715\n",
      "need to widen edge circle beyond 0.0018731240504440464 for tract (x,y)=( -122.26724536122664 37.54886792560715\n",
      "need to widen edge circle beyond 0.0020604364554884513 for tract (x,y)=( -122.26724536122664 37.54886792560715\n",
      "did not find boundary with circle approach.  Brute-force it.\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 8969 2.0 3 90.0 0.1776 26979.0\n",
      "I am working on tract number 8980 of 9129 tracts\n",
      "I am working on tract number 9000 of 9129 tracts\n",
      "I am working on tract number 9020 of 9129 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 9021 5.0 3 -243.9 0.5147 264264.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 9021 6.0 3 -243.9 0.4985 264264.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 9021 7.0 3 -243.9 0.4828 264264.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 9021 8.0 3 -243.9 0.4676 264264.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 9021 9.0 3 -243.9 0.4528 264264.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 9021 10.0 3 -243.9 0.4386 264264.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 9021 11.0 3 -243.9 0.4247 264264.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 9021 12.0 3 -243.9 0.4113 264264.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 9021 13.0 3 -243.9 0.3984 264264.8\n",
      "we have 2 non-opposing shorted wedges for tract no 9026\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 9028 4.0 3 42.0 0.2064 30995.8\n",
      "we have 2 non-opposing shorted wedges for tract no 9029\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 9031 8.0 3 91.4 0.3648 126487.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 9031 11.0 0 88.6 0.1581 198308.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 9031 12.0 0 88.6 0.1657 198308.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 9032 5.0 1 90.0 0.2976 167232.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 9032 6.0 1 90.0 0.3271 167232.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 9032 7.0 1 90.0 0.3596 167232.3\n",
      "I am working on tract number 9040 of 9129 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 9054 1 208318.81906984615 0.4548\n",
      "8 yoyos for tract,wedge,wedgePop,r= 9054 1 298470.35037584696 0.9573\n",
      "8 yoyos for tract,wedge,wedgePop,r= 9054 1 267519.7409282025 0.7061\n",
      "8 yoyos for tract,wedge,wedgePop,r= 9054 1 258015.23563510494 0.5804\n",
      "8 yoyos for tract,wedge,wedgePop,r= 9054 1 248811.59501396812 0.5176\n",
      "8 yoyos for tract,wedge,wedgePop,r= 9054 1 241227.5868926128 0.4862\n",
      "8 yoyos for tract,wedge,wedgePop,r= 9054 1 236382.01392323436 0.4705\n",
      "I am working on tract number 9060 of 9129 tracts\n",
      "I am working on tract number 9080 of 9129 tracts\n",
      "I am working on tract number 9100 of 9129 tracts\n",
      "I am working on tract number 9120 of 9129 tracts\n",
      "Sum of weights over all precinct home districts should have been 1.000, but was  1.0000466595248172\n",
      "Average and max number of wedgePop loops per tract were:  8.079417241757039 40.0\n",
      "min,average,max of Home District areas were:  0.0 1.0515846864571867 17.000708115617513\n",
      "calculated statewide vote was 0.35294274066213743, should have been 0.3509058667735862\n",
      "calcd statewide Hispanic pop was 0.3522410992316589, should have been 0.359530744129233\n",
      "calcd statewide Black pop was 0.05570057861475917, should have been 0.0570201775353216\n",
      "fraction of HDs that with altered wedge angles near boundaries =  0.23058385365319312\n"
     ]
    }
   ],
   "source": [
    "#3/13/22 - HD1: using coeff1, coeff2 (unrestricted opp wedge pop, wideAngle quadratic in ratio)\n",
    "# Bisect for yoyo > 3, precinct calcs after wedges finalized.  More aggressive Euler gain\n",
    "#minTractPop = 10  #this is set in a prior block\n",
    "pi=3.1415926536\n",
    "nWedges = 4  #number of wedges per home district polygon  \n",
    "avgWedgeAngle = 2*pi / nWedges\n",
    "wedgeTriAR = [math.sin(pi/nWedges)*math.cos(pi/nWedges)]*nWedges  #wedge triangle area ratio (= area / r*r)\n",
    "angle = [0.]*nWedges\n",
    "angle2 = [0.]*nWedges\n",
    "pt1 = [Point(0,0)]*nWedges  #these four define the polygon wedge for a growing home district\n",
    "pt2 = [Point(0,0)]*nWedges\n",
    "pt3 = [Point(0,0)]*nWedges\n",
    "pt4 = [Point(0,0)]*nWedges\n",
    "oldR = [0.]*nWedges  #wedge radius from previous loop\n",
    "# guessedR = [0.]*nWedges  #obsolete; was wedge radius if we extrapolate from population density of most recent wedge piece\n",
    "printPoly = [Polygon([(0,0),(0,1),(1,1)])]*nWedges #for debugging\n",
    "wedgePop = [0.]*nWedges\n",
    "tractLoopCounter = [0.]* nTracts  #this tracks how many loops per tract to get to target wedge Pop\n",
    "nearEdge = [0.]* nTracts   #not yet implemented; this will flag tracts near map edge for reprocessing\n",
    "tractUse = [0.] * nTracts  #this will store how much we use this tract in ALL HD's vs. expectation\n",
    "precinctUse = [0.] * nPrecincts   #same, but for each precinct / VTD\n",
    "loopTractUse = [0.] * nTracts  #same as above two, but only for the current loop / tract\n",
    "loopPrecinctUse = [0.] * nPrecincts\n",
    "HDvPop = [0.]*nTracts\n",
    "HDvGOP = [0.]*nTracts  #GOP lean of each tract's \"home district\"\n",
    "HDvBlack = [0.]*nTracts\n",
    "HDvHisp = [0.]*nTracts #pct Hispanic by home district\n",
    "HDweight = [0.]*nTracts  #relative weight of each district.  In absence of splits, will equal precinct pop\n",
    "HDarea = [0.]*nTracts  #geographical area of each home district\n",
    "HDradius = [[0.]*nWedges for t in range(nTracts)] #final wedge length for each Home District wedge\n",
    "HDangle = [[0.]*nWedges for t in range(nTracts)] #final included angle for each HD wedge\n",
    "angle0 = [-999.] * nTracts  #orientation of 0th wedge.  Random except re-oriented if we are near-boundary\n",
    "toler = 0.005  #adjustable - fractional slop in district population.  normally 0.01, to be reduced to 0.005\n",
    "tolerPop = toler * avgDistrictPop  #absolute slop in district pop\n",
    "nLoopPrint = 30  #at this loop number, we alert user of problem\n",
    "nGiveUp = 40  #we punt after this many loops\n",
    "nLoopSuperPrint = nGiveUp - 2 # at this loop number, we output wedge growth visuals\n",
    "wrongPop = [0.]*nTracts\n",
    "normalGain = 0.8  #adjustable - a bit less than 1.0 for stability, how far we step relative to expected perfect guess\n",
    "EulerGain = 1.5 #if we hit empty land, gain more aggressively to get through it\n",
    "#yoyoFactor = 0.3 #rate of reduction in gain as solver continues to yoyo in solving a wedge  #not currently used ***\n",
    "globalMax_dr = (MAP.area/nDistricts) ** 0.5  #put a reasonable upper limit on wedge radial growth step size\n",
    "tractPrintInterval = 20  #for tracking progress\n",
    "minTractArea = 0.00001 * MAP.area / nTracts  #failsafe for later div-by-zero\n",
    "homePopDensity = avgGridDensity  #seed this\n",
    "didWeRestart = [0] * nTracts  #will flag if we adjusted wedge angles due to a single shorted wedge\n",
    "coeff1 = 0.3  #linear term. we will adjust this empirically to tighten tract weighting near boundaries\n",
    "coeff2 = 0.3  #quadratic term.  These two control distortion in wedge angles relative to wedgePop shortness\n",
    "minWedgePop = [avgDistrictPop/nWedges] * nTracts  #wedge pop for wedge facing boundary (for tracts near boundaries)\n",
    "maxWideAngle = 0.8 * pi  #adjustable parameter.  (avoid wedges too close to half a pie\n",
    "\n",
    "for t in range(nTracts) :  #(nTracts):  #loop on each tract.  Start by resetting stats\n",
    "    gain = normalGain  #in case last precinct had convergence problems\n",
    "    if (t % tractPrintInterval) == 0 : \n",
    "        print(\"I am working on tract number {0} of {1} tracts\".format(t,nTracts) )\n",
    "    tractLoopCounter[t] = 0.  #for stability stats, will track how many times we need to loop for each tract\n",
    "    # isActiveG = [0]*nGrids  #resets whether each grid is relevant to this tract (not used; see alt grid turn-on method)\n",
    "    if (tractArea[t] > minTractArea) :  #too lazy to indent everything.  We'll catch zero tractArea later\n",
    "        homePopDensity = tractPop[t]/tractArea[t]  #temporary - estimate the local density for initial step\n",
    "    tractCP = Point(tractGeom[t].centroid.x,tractGeom[t].centroid.y)  #shorthand for centroid of each tract\n",
    "    for nG in range(nGrids):\n",
    "        if gridGeom[nG].contains(tractCP) :  #which grid contains the centroid of this tract?  Turn it on!\n",
    "            # isActiveG[nG] = 1  #I don't think I use this\n",
    "            homeGridDensity = gridDensity[nG]\n",
    "    maxStartDensity = max(homePopDensity,homeGridDensity)\n",
    "    minR = (avgDistrictPop / maxStartDensity / pi)**0.5   # conservative estimated radius of this tract's district\n",
    "    tinyR = 0.01 * minR   #ensures we start with small, but not infinitesimal wedge populations\n",
    "    angle0[t] = random.uniform(0,2.*pi)  #imparts random orientation to our starting wedge\n",
    "    loopTractUse = [0.]*nTracts  #this and below help us reset tract n precinct use after a wedge reset\n",
    "    loopPrecinctUse = [0.]*nPrecincts\n",
    "    # ***GROW WEDGES SIMULTANEOUSLY via ARRAYS, SO WE CAN REACT ON FLY TO BOUNDARY STOPS\n",
    "    HDpop = 0.  #running total of this tract's \"home district\" population\n",
    "    nActiveWedges = nWedges #active wedges have not run over boudnary\n",
    "    targetWedgePop = [avgDistrictPop / nWedges]*nWedges  #at beginning, split districtPop equally among wedges\n",
    "    #latestWedgeDensity = [0.]*nWedges  #stop using # pop'n density of the wedge piece we just added or subtracted\n",
    "    wedgePop = [0.]*nWedges\n",
    "    oldWedgePop = [0.]*nWedges  #wedge pop from previous round (needed for NR projection)\n",
    "    wedgePopGap = [0.]*nWedges\n",
    "    isOverEdge = [0] *nWedges #each wedge is still fully inside map boundary\n",
    "    isSatisfied = [0] * nWedges #wedges close enough to target are not improved upon\n",
    "    yoyoCount = [0] * nWedges #tracks how many times we've reversed this wedge's growth vs. shrink at current wPop target\n",
    "    wedgeMaxR = [0.] * nWedges #will track the largest radius this wedge has seen (to cap yoyo bisection step)\n",
    "    wedgeAngle = [avgWedgeAngle] * nWedges #reset to equi-angle when starting each tract    \n",
    "    currentR = [0.]*nWedges\n",
    "    old_dr = [0.]*nWedges\n",
    "    wedgeStop = 0  #obsolete? this will flag if we need to rejigger oldR when we stopped an over-boundary wedge\n",
    "    for nW in range(nWedges):\n",
    "        currentR[nW] = tinyR  #each wedge starts as a tiny triangle of this radius\n",
    "        old_dr[nW] = currentR[nW] #this will track the last radial step (to help convergence)\n",
    "    oldR = [0.]*nWedges   #for remembering last loop's wedge radius\n",
    "    max_dr = [globalMax_dr]*nWedges  #reset max possible positive radial step size\n",
    "    for nW in range(nWedges) :  #this loop: set up tiny wedges in each direction to seed each wedge loop\n",
    "        angle[nW] = (nW-0.5)*wedgeAngle[nW]+angle0[t]   #local variable for orientation of START of wedge\n",
    "        angle2[nW] = angle[nW]+wedgeAngle[nW]      #local angle for clockwise END of wedge\n",
    "        pt1[nW] = tractCP\n",
    "        pt2[nW] = Point(tractCP.x+currentR[nW]*math.cos(angle[nW]),  tractCP.y+currentR[nW]*math.sin(angle[nW]) )\n",
    "        pt3[nW] = Point(tractCP.x+currentR[nW]*math.cos(angle2[nW]), tractCP.y+currentR[nW]*math.sin(angle2[nW]) )\n",
    "        wedgePoly = Polygon([pt1[nW], pt2[nW], pt3[nW] ]) #build a tiny starter wedge triangle\n",
    "        wedgePop[nW] = tractPop[t]* wedgePoly.area/max(tractArea[t],minTractArea)  #max prevents rare div-by-zero\n",
    "    HDpop = np.sum(wedgePop)\n",
    "    if (tractPop[t] < minTractPop or tractArea[t] == 0 or isSkippedTract[t] == 1):\n",
    "        #go directly to jail, do not pass Go, this tract doesn't count\n",
    "        HDpop = avgDistrictPop  #white lie to kick us out of loop\n",
    "    while abs (HDpop - avgDistrictPop) > tolerPop :  #until we've grown the home district to the right size...\n",
    "        sumWedgePopGapChange = 0  #this will total wedge pops that fall short of expectations (when over boundary)\n",
    "        for nW in range(nWedges) :  #for each wedge, we'll build to gain pop or shrink to lose population ...\n",
    "            neededWedgePop = targetWedgePop[nW] - wedgePop[nW]\n",
    "            isSatisfied[nW] = 0  #default in case target changed last loop.  We'll check immediately below\n",
    "            if abs(neededWedgePop/targetWedgePop[nW]) < 0.5*toler :  #is this wedge close enough to stop iterating on it?\n",
    "                isSatisfied[nW] = 1\n",
    "            if isOverEdge[nW] == 0 and isSatisfied[nW] == 0:   #we skip over-boundary and near-perfect wedges\n",
    "                wedgePopDelta = wedgePop[nW] - oldWedgePop[nW]  #how much wedgePop gained in last loop\n",
    "                if (wedgePopDelta == 0): #our last wedge change was in an empty area (desert or off map)\n",
    "                    gainAdjust = EulerGain/gain  #Euler method often over-cautious at map edges or in sparse areas\n",
    "                    guessedRsquared = currentR[nW]*currentR[nW] * targetWedgePop[nW] / wedgePop[nW]  #Euler guess\n",
    "                    # can't use Newton-Raphson since last dy was zero, use Euler instead\n",
    "                    print(\"we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop\",t,tractLoopCounter[t],\n",
    "                          nW, round(180./pi*wedgeAngle[nW],1),round(currentR[nW],4),round(wedgePop[nW],1))\n",
    "                else: #use N-R estimation\n",
    "                    gainAdjust = 1.0\n",
    "                    R2delta = currentR[nW]*currentR[nW] - oldR[nW]*oldR[nW]  #this and below are run/rise of current slope\n",
    "                    guessedRsquared = currentR[nW]*currentR[nW] + R2delta / wedgePopDelta * neededWedgePop\n",
    "                    \n",
    "                guessedRsquared = max( guessedRsquared, 0. ) #minimum guardrail\n",
    "                guessed_dr = guessedRsquared ** 0.5 - currentR[nW]  #best guess for wedge radius change\n",
    "                #gain = max(0.3,normalGain ** (1. + yoyoFactor * yoyoCount[nW]))  #obsolete; using bisect\n",
    "                dr = gain * gainAdjust * guessed_dr   #gain typically ~0.8 for stability\n",
    "                dr = max( -0.5*currentR[nW],min(dr,max_dr[nW]) )  #apply min and max guardrails to wedge radius change\n",
    "                \n",
    "                if np.sign(dr) != np.sign(old_dr[nW]) :  #are we yoyoing? How many times?\n",
    "                    yoyoCount[nW] += 1\n",
    "                if yoyoCount[nW] > 3 and yoyoCount[nW] <= 6 :\n",
    "                    wedgeMaxR[nW] = max(wedgeMaxR[nW],currentR[nW]) #will track largest R in yoyo cycle\n",
    "                    max_dr[nW] = 2.*wedgeMaxR[nW]  #this will now store a reasonable max bisection step size\n",
    "                if yoyoCount[nW] > 6 :  #switch to bisection method; too many yo-yo's\n",
    "                    print(yoyoCount[nW],\"yoyos for tract,wedge,wedgePop,r=\",t,nW,wedgePop[nW],round(currentR[nW],4) )\n",
    "                    max_dr[nW] = 0.5 * max_dr[nW] #we are now bisecting ...\n",
    "                    if(neededWedgePop < 0):\n",
    "                        dr = max(-1.*max_dr[nW], -0.5*currentR[nW])  #reduce wedge size\n",
    "                    else:\n",
    "                        dr = max_dr[nW]  #increase wedge size\n",
    "                old_dr[nW] = dr  #these three lines -- save current as old values for next loop\n",
    "                oldR[nW] = currentR[nW]\n",
    "                oldWedgePop[nW] = wedgePop[nW]\n",
    "                if dr > 0. :  #we are growing a wedge trapezoid piece \n",
    "                    outerR = currentR[nW] + dr\n",
    "                    innerR = currentR[nW]\n",
    "                    currentR[nW] = outerR    #for next loop around\n",
    "                else:    #this wedge trapezoid piece will be SUBTRACTED from current wedge\n",
    "                    outerR = currentR[nW]\n",
    "                    innerR = currentR[nW] + dr  #remember, dr is negative here\n",
    "                    currentR[nW] = innerR             #for next loop around\n",
    "                #now, describe the new wedge to probe for precinct intersections ...\n",
    "                pt1[nW] = Point(tractCP.x+innerR*math.cos(angle[nW]), tractCP.y+innerR*math.sin(angle[nW]) )\n",
    "                pt2[nW] = Point(tractCP.x+outerR*math.cos(angle[nW]), tractCP.y+outerR*math.sin(angle[nW]) )\n",
    "                pt3[nW] = Point(tractCP.x+outerR*math.cos(angle2[nW]),tractCP.y+outerR*math.sin(angle2[nW]) )\n",
    "                pt4[nW] = Point(tractCP.x+innerR*math.cos(angle2[nW]),tractCP.y+innerR*math.sin(angle2[nW]) )\n",
    "                wedgePoly = Polygon([pt1[nW], pt2[nW], pt3[nW],pt4[nW]])  #true for wedge add-on or to-be-trimmed\n",
    "                \n",
    "                printPoly[nW] = wedgePoly  #for debugging\n",
    "                latestWedgePop = 0.  #for the new piece, not the entire triangle\n",
    "                usedTract = [0]*nTracts  #rezero lists of tracts and precincts that could straddle multiple grids\n",
    "                usedPrecinct = [0]*nPrecincts\n",
    "                for nG in range(nGrids) :  # loop over ACTIVE grids to look for intersecting tracts\n",
    "                    gridIntersxn = gridGeom[nG].intersection(wedgePoly)\n",
    "                    if (gridIntersxn.area > 0) :  #this grid is RELEVANT to this wedge\n",
    "                        for tt in range(nGridTracts[nG]) : #look for intersxns with all tracts in this grid\n",
    "                            nTT = gridTractNo[nG][tt] #shorthand for this tract's global tract no\n",
    "                            if(usedTract[nTT] == 0) :  #Did we not already look at this tract in another grid list?\n",
    "                                usedTract[nTT] = 1  #well, now we have!  Probe intersection with wedge\n",
    "                                overlap = tractGeom[nTT].intersection(wedgePoly).area\n",
    "                                if overlap > 0 :\n",
    "                                    fracArea = overlap/tractArea[nTT]\n",
    "                                    latestWedgePop  += fracArea*tractPop[nTT]  #always positive (used in density calc)\n",
    "                                    loopTractUse[nTT] += np.sign(dr)*overlap/tractArea[nTT] * tractPop[t]/avgDistrictPop\n",
    "                        # found all possible tract overlaps with this increment / decrement to this wedge.\n",
    "                        \n",
    "                wedgePop[nW] += np.sign(dr)*latestWedgePop  #for full triangle, based on this latest piece\n",
    "                # Now, flag if we're beyond boundary\n",
    "                if wedgePop[nW] < targetWedgePop[nW] : #if growing, confirm we're not beyond MAP boundary\n",
    "                    leadingEdge = LineString([pt2[nW],pt3[nW]])\n",
    "                    if leadingEdge.intersects(MAP) :  #still room to grow in part of edge, keep going\n",
    "                        gerrymandering = \"evil\"  #it had to be said\n",
    "                    else:  #this wedge is fully beyond the map. give up on more map intersection\n",
    "                        isOverEdge[nW] = 1\n",
    "                        shortedWedge = nW  #ID'ing highest numbered wedge that got shorted by the boundary in this loop\n",
    "                        oldWedgePopGap = wedgePopGap[nW]\n",
    "                        wedgePopGap[nW] = targetWedgePop[nW] - wedgePop[nW]  #how far this wedge's pop is below its target\n",
    "                        nActiveWedges -= 1  #a few lines below, we will adjust other wedge's targets\n",
    "                        sumWedgePopGapChange += wedgePopGap[nW] - oldWedgePopGap\n",
    "                        if (nActiveWedges == 0) : #we're doomed, somehow all wedges are short and off map\n",
    "                            print(\"PUNT! no more active wedges for tract, loop =\",t,tractLoopCounter[t] )\n",
    "                            tractLoopCounter[t] = nGiveUp + 1  #PUNT !!!\n",
    "                            \n",
    "                        max_dr = [globalMax_dr]*nWedges   #allow other wedges to take big steps again to catch up\n",
    "                        yoyoCount = [0] * nWedges  #go back to original gains on ALL active wedges\n",
    "                   \n",
    "        # end of nW loop to adjust all wedge populations by growing or trimming wedges, IDing over-edge wedges\n",
    "        tractLoopCounter[t] +=1   # still looping on home district Pop.\n",
    "        nReceivingWedges = nActiveWedges\n",
    "        oppFlag = 0\n",
    "        if 0 == 1: #always false; for HD2 we would have checked here for opp wedge restriction; ignore this block\n",
    "            # targetWedgePop[int(nWedges/2)] < 0.99 * avgDistrictPop/float(nWedges): #is opp wedge restricted?\n",
    "            oppFlag = 1\n",
    "            nReceivingWedges -= 1-isOverEdge[int(nWedges/2)]  #if yes, don't count opposite wedge as a receiver\n",
    "        if nReceivingWedges == 0: #rarely, the opposite wedge is the only active one\n",
    "            for nWW in range(nWedges): #in this case, we allow the opposite wedge to pick up the slack\n",
    "                targetWedgePop[nWW] += sumWedgePopGapChange/max(1.,float(nReceivingWedges) )\n",
    "        else: #if the opp wedge has a ceiling wedgePopTarget, distribute wedgePopGap to other active wedges\n",
    "            for nWW in range(nWedges):  #time to make adjustments in target wedge pops based on boundary fails\n",
    "                if nWW != int(nWedges/2) or oppFlag == 0 :  #excluding flagged opposite wedge as a receiver\n",
    "                    targetWedgePop[nWW] += sumWedgePopGapChange/float(nReceivingWedges)\n",
    "\n",
    "        # *** NEW 1/19/22 CODE TO ADJUST WEDGE ANGLES WHEN A BOUNDARY ENCOUNTERED\n",
    "        if (nActiveWedges == nWedges or nActiveWedges < nWedges - 2\n",
    "           or didWeRestart[t] == 1) :  #0 or 3+ over-boundary short wedges, or we've already adjusted wedge angles once\n",
    "            HDpop = np.sum(wedgePop) #Keep going with normal wedge growth and trim process\n",
    "        else :  # 1 OR 2 SHORTED WEDGES.  MAY WANT TO ALTER WEDGE ANGLES\n",
    "            didWeRestart[t] = 1  #to ensure we adjust wedge angles and target wedgePops at most once per tract\n",
    "            if (nActiveWedges == nWedges - 2) :  #exactly two wedges got shorted in this loop -- are they opposing?\n",
    "                oppW = int( (shortedWedge + nWedges/2) % nWedges)  #the index of wedge opposite the last shorted wedge\n",
    "                if (isOverEdge[oppW] == 0) :\n",
    "                    print(\"we have 2 non-opposing shorted wedges for tract no\",t)\n",
    "                    totalLiveAngle = 2.*pi - np.sum(isOverEdge)*avgWedgeAngle  #avail angle to divvy among live wedges  \n",
    "                    for nW in range (nWedges) : #Decrease wedge angles opposite shorted wedges via a complex weighting\n",
    "                        if isOverEdge[nW] == 0 :\n",
    "                            oppW = int( (nW + nWedges/2) % nWedges) \n",
    "                            angleWeight = (np.sum(wedgePopGap)-wedgePopGap[oppW])/np.sum(wedgePopGap)/(nActiveWedges-1)\n",
    "                            wedgeAngle[nW] = angleWeight * totalLiveAngle  \n",
    "                else : #shorted wedges ARE opposing\n",
    "                    print(\"we have 2 OPPOSING shorted wedges for tract no\",t) # no wedge-angle adjustment in this case\n",
    "                    #wedgeAngle=[avgWedgeAngle]*nWedges  #comment this out, no change\n",
    "            else: # a single shorted wedge (over boundary).  COMPLETELY RESTART wedge growth process\n",
    "                shortW = shortedWedge #Next dozen lines: convoluted code to find angle to closest boundary point\n",
    "                #print(\"1 wedge over map boundary for tract\",t,\"at loop, wedgePop\",tractLoopCounter[t],wedgePop[shortW] )\n",
    "                shortedPoly = Polygon([tractCP, pt2[shortW],pt3[shortW] ])\n",
    "                MAPedge = shortedPoly.intersection(MAP.exterior) #true state boundary line where wedge crossed it\n",
    "                minDistance = max(tractCP.distance(MAPedge),tinyR)  #closest distance to edge where wedge hit the boundary\n",
    "                edgeCircle = tractCP.buffer(1.01*minDistance)  #build a circle a little bigger than this distance\n",
    "                #  1.001 is not big enough; will occasionally not intersect\n",
    "                closeArea = edgeCircle.intersection(MAPedge)\n",
    "                counter = 0.\n",
    "                maxCounter = 10. #give up after 10 tries\n",
    "                while closeArea.is_empty :  # protect against missing the map boundary somehow\n",
    "                    print(\"need to widen edge circle beyond\",minDistance, \"for tract (x,y)=(\",tractCP.x,tractCP.y)\n",
    "                    minDistance = minDistance * 1.1\n",
    "                    edgeCircle = tractCP.buffer(minDistance)  #widen the circle\n",
    "                    closeArea = edgeCircle.intersection(MAPedge)\n",
    "                    counter += 1\n",
    "                    if counter >= maxCounter: #not finding map edge intersection.  Try another way\n",
    "                        print(\"did not find boundary with circle approach.  Brute-force it.\")\n",
    "                        minDistance = tractCP.distance(MAP.exterior)\n",
    "                        edgeCircle = tractCP.buffer(1.01*minDistance)\n",
    "                        closeArea = edgeCircle.intersection(MAP.exterior)                        \n",
    "            \n",
    "                closePoint = closeArea.centroid  # this is a point very close to the closest beeline from tract to map edge\n",
    "                #print(closePoint,tractCP, \"are boundary point and tract center point\")\n",
    "                x1 = closePoint.x\n",
    "                x2 = tractCP.x  #debugging\n",
    "                dx = closePoint.x - tractCP.x\n",
    "                dy = closePoint.y - tractCP.y\n",
    "                exitAngle = pi/2. * np.sign(dy)  #default in case dx=0\n",
    "                if (dx != 0 ):\n",
    "                    exitAngle = math.atan(dy/dx)  #this is the angle from the x-axis to the exit beeline\n",
    "                    if dx < 0 :  #use complementary atan solution; boundary is west of tract centroid\n",
    "                        exitAngle = pi + exitAngle\n",
    "                angle0[t] = exitAngle # this reorients 0th wedge to face boundary's closest point               \n",
    "                # New 1/23/22 - let's estimate wedgePopGap at ideal orientation, normal angle   # ****************\n",
    "                wedgeAngle1 = exitAngle - 0.5*avgWedgeAngle\n",
    "                wedgeAngle2 = exitAngle + 0.5*avgWedgeAngle\n",
    "                maxR = max(stateWidth,stateHeight) #ensuring we make a big enough wedge\n",
    "                wedgePt1 = tractCP\n",
    "                wedgePt2 = Point(tractCP.x+maxR*math.cos(wedgeAngle1),  tractCP.y+maxR*math.sin(wedgeAngle1) )\n",
    "                wedgePt3 = Point(tractCP.x+maxR*math.cos(wedgeAngle2), tractCP.y+maxR*math.sin(wedgeAngle2) )\n",
    "                wedgePoly = Polygon([ wedgePt1, wedgePt2, wedgePt3 ])\n",
    "                minWedgePop[t] = 0. #the wedgePop of the shorted wedge if we re-orient but don't adjust angles\n",
    "                usedTract = [0]*nTracts  #rezero lists of tracts and precincts that could straddle multiple grids\n",
    "                for nG in range(nGrids) :  # loop over ACTIVE grids to look for intersecting tracts\n",
    "                    gridIntersxn = gridGeom[nG].intersection(wedgePoly)\n",
    "                    if (gridIntersxn.area > 0) :  #this grid is RELEVANT to this wedge\n",
    "                        for tt in range(nGridTracts[nG]) : #look for intersxns with all tracts in this grid\n",
    "                            nTT = gridTractNo[nG][tt] #shorthand for this tract's global tract no\n",
    "                            if(usedTract[nTT] == 0) :  #Did we not already look at this tract in another grid list?\n",
    "                                usedTract[nTT] = 1  #well, now we have!  Probe intersection with wedge\n",
    "                                overlap = tractGeom[nTT].intersection(wedgePoly).area\n",
    "                                if overlap > 0 :\n",
    "                                    fracArea = overlap/tractArea[nTT]\n",
    "                                    minWedgePop[t]  += fracArea*tractPop[nTT]  #always positive (used in density calc)\n",
    "                #print(\"the minimum shorted Wedge Pop for tract {0} is {1}\".format(t,minWedgePop[t]) )  #debug\n",
    "                #printAngle[t] = round(exitAngle*180./pi,4) #for debugging\n",
    "                printDist = round(minDistance,4)\n",
    "                #print(t,\"(\",tractCP.x,tractCP.y,\")\",printAngle,printDist,\"t,tract(x,y),exitAngle,dist\")\n",
    "                # ********************************************************************\n",
    "                # assign new wedge angles.  The two wide angles face toward and away from nearest boundary\n",
    "                #ratio = wedgePopGap[shortW]/ (avgDistrictPop/nWedges)  #0-1; this is degree of shortness\n",
    "                ratio = 1. - minWedgePop[t]/ (avgDistrictPop/nWedges)  # *** UPDATED\n",
    "                # printWedgePopGap[t] = wedgePopGap[shortW]\n",
    "                wideAngle = (1. + coeff1 * ratio + coeff2 * ratio*ratio)*avgWedgeAngle #HERE, WE ADJUST ANGLES\n",
    "                wideAngle = min(wideAngle, maxWideAngle*pi) #set an upper limit\n",
    "                thinAngle = (2.*pi - 2.*wideAngle)/(nWedges - 2.)  #other wedges equally angle-compressed\n",
    "                #if (t % 9 == 0):  #occasional print\n",
    "                    #print(\"tract,wide, thin angles are \",t,round(180/pi*wideAngle,4),round(180/pi*thinAngle,4) )\n",
    "                for nW in range(nWedges) :\n",
    "                    if (nW == 0 or nW == int(nWedges/2) ) : #assign these two as shorted wedge and its opposite\n",
    "                        wedgeAngle[nW] = wideAngle\n",
    "                    else :\n",
    "                        wedgeAngle[nW] = thinAngle\n",
    "                #** COMPLETELY RESTART WEDGE GROWTH PROCESS FROM INITIAL PIZZA SLICES, NOW RE-ORIENTED\n",
    "                loopTractUse = [0.] * nTracts  # reset as we are starting over\n",
    "                loopPrecinctUse = [0.]* nPrecincts\n",
    "                HDpop = 0.\n",
    "                nActiveWedges = nWedges\n",
    "                targetWedgePop = [avgDistrictPop/nWedges] * nWedges\n",
    "                oldR = [0.]*nWedges   #for remembering last loop's wedge radius  \n",
    "                currentR = [tinyR]*nWedges                \n",
    "                old_dr = [tinyR]*nWedges  #this will track the last radial step (to help convergence)\n",
    "                max_dr = [globalMax_dr]*nWedges  #reset max step size\n",
    "                wedgePop = [0.]*nWedges\n",
    "                oldWedgePop = [0.]*nWedges #wedge pop from previous round\n",
    "                wedgePopGap = [0.]*nWedges\n",
    "                isOverEdge = [0] *nWedges\n",
    "                isSatisfied = [0] *nWedges\n",
    "                yoyoCount = [0] *nWedges #just in case we missed this earlier\n",
    "                wedgeMaxR = [0.] * nWedges #resetting\n",
    "                angle[0] = angle0[t] - 0.5*wideAngle  #the 0th wedge always faces the boundary\n",
    "                angle2[0] = angle[0] + wedgeAngle[0]\n",
    "                for nW in range(nWedges) :\n",
    "                    if (nW == 0):\n",
    "                        angle[nW] = angle0[t] - 0.5*wideAngle  #we have to start somewhere :-)\n",
    "                    else :\n",
    "                        angle[nW] = angle2[nW-1]\n",
    "                    angle2[nW] = angle[nW]+wedgeAngle[nW]      \n",
    "                    pt1[nW] = tractCP\n",
    "                    pt2[nW] = Point(tractCP.x+tinyR*math.cos(angle[nW]),  tractCP.y+tinyR*math.sin(angle[nW]) )\n",
    "                    pt3[nW] = Point(tractCP.x+tinyR*math.cos(angle2[nW]), tractCP.y+tinyR*math.sin(angle2[nW]) )\n",
    "                    wedgePoly = Polygon([pt1[nW], pt2[nW], pt3[nW] ])\n",
    "                    wedgePop[nW] = tractPop[t]* wedgePoly.area/max(tractArea[t],minTractArea)\n",
    "                HDpop = np.sum(wedgePop)   #** END OF RESTART BLOCK.  RE-ENTER MAIN LOOP FOR THIS TRACT\n",
    "                      \n",
    "        # **** BELOW IS TO CORRECT FOR NONCONVERGENCE *****\n",
    "        if (tractLoopCounter[t] > nLoopPrint):  #may be becoming unstable. Alert user,    #and (don't) reduce gain\n",
    "            strPop = str(round(HDpop,2))\n",
    "            strWdg = \"Overedge?\"\n",
    "            strSat = \"Satisfied?\"\n",
    "            strYoyo = \"yoyo?\"                \n",
    "            strTWP_dr = \"tWP,dr\"\n",
    "            for nWW in range(nWedges) :\n",
    "                strPop = strPop + \", \"+str(round(wedgePop[nWW],1) )\n",
    "                strWdg = strWdg +str(isOverEdge[nWW])+\", \"\n",
    "                strSat = strSat +str(isSatisfied[nWW])\n",
    "                strYoyo = strYoyo + str(yoyoCount[nWW])\n",
    "                strTWP_dr = strTWP_dr + \", \"+str(round(targetWedgePop[nWW],1) )+\",\"+str(round(old_dr[nWW],4) )\n",
    "            print(\"loop{0}, tr{1},wedgePops{2}, {3},{4},{5} \".format(tractLoopCounter[t],t,strPop,strWdg,strSat,strYoyo) )\n",
    "            print(\"   targetWP, latest drx4 are\",strTWP_dr)\n",
    "\n",
    "        if (tractLoopCounter[t] > nLoopSuperPrint) :\n",
    "            for nWW in range(nWedges):                \n",
    "                print(\"wedge no, currentR,oldWedgePop, wedgePop, overEdge?\",nWW,str(round(currentR[nWW],5)), \n",
    "                      str(round(oldWedgePop[nWW],4)), str(round(wedgePop[nWW],4)),isOverEdge[nWW])   #debug\n",
    "                x, y = printPoly[nWW].exterior.xy     #wedge debugging .....\n",
    "                plt.plot(x, y, c=(0.1, 0.2, 0.02+float(nWW)/nWedges) )\n",
    "            plt.show()\n",
    "        if(tractLoopCounter[t] >= nGiveUp):\n",
    "            print(\"I looped {0} times on tract {1}, giving up w pop {2}\".format(nGiveUp,t,HDpop) )\n",
    "            wrongPop[t] = HDpop  #this will flag this HD as triaged\n",
    "            HDpop = avgDistrictPop  #white lie to kick out of loop\n",
    "        # *** END OF TRIAGE FOR NONCONVERGENCE\n",
    "        \n",
    "    # END OF WHILE LOOP --> we are within tolerance of avgDistrictPop. Finalize this tract's Home District stats\n",
    "    for nTT in range (nTracts) :\n",
    "        tractUse[nTT] += loopTractUse[nTT]\n",
    "    totGOP = 0.\n",
    "    totVote = 0.\n",
    "    totVAP = 0.\n",
    "    totHisp = 0.\n",
    "    totBlack = 0.  #zero these out prior to summing over final wedges\n",
    "    usedTract = [0]*nTracts  #rezero lists of tracts and precincts that could straddle multiple grids\n",
    "    usedPrecinct = [0]*nPrecincts\n",
    "\n",
    "    if (tractPop[t] < minTractPop or tractArea[t] == 0 or isSkippedTract[t] == 1): \n",
    "        #we bypassed the big loop; this tract is inconsequential\n",
    "        HDvPop[t] = HDpop  #a white lie\n",
    "        HDweight[t] = 0.000001  #to suppress this in total stats\n",
    "    else :\n",
    "        HDvPop[t] = np.sum(wedgePop)\n",
    "        # HDvHisp[t] = np.sum(wedgeHisp)/np.sum(wedgePop)  #3/2/22 - move to final wedge calcs\n",
    "        # HDvBlack[t] = np.sum(wedgeBlack)/np.sum(wedgePop)  #3/2/22 - move to final wedge calcs\n",
    "        HDweight[t] = tractPop[t]/np.sum(tractPop)\n",
    "        nearEdge[t] = nWedges - nActiveWedges  #flagging the number of wedges that were not completely pop-filled\n",
    "        centerPt = tractCP\n",
    "        outerPt2 = Point(tractCP.x+currentR[0]*math.cos(angle[0]), tractCP.y+currentR[0]*math.sin(angle[0]) )\n",
    "        outerPt3 = Point(tractCP.x+currentR[0]*math.cos(angle2[0]),tractCP.y+currentR[0]*math.sin(angle2[0]) )\n",
    "        HDpolly = Polygon([centerPt,outerPt2,outerPt3])   #initiate a polygon that will be the home district\n",
    "        for nW in range(nWedges):\n",
    "            HDradius[t][nW] = currentR[nW]\n",
    "            HDangle[t][nW] = angle[nW]\n",
    "            \n",
    "        for nW in range(1,nWedges):  #save final geometry, compute minority and partisan stats\n",
    "            cR = currentR[nW] #shorthand\n",
    "            outerPt2 = Point(tractCP.x+cR*math.cos(angle[nW]), tractCP.y+cR*math.sin(angle[nW]) )\n",
    "            outerPt3 = Point(tractCP.x+cR*math.cos(angle2[nW]),tractCP.y+cR*math.sin(angle2[nW]) )\n",
    "            HDpolly =  HDpolly.union( Polygon([centerPt,outerPt2,outerPt3]) )  #add this wedge to HD district polygon\n",
    "        HDpolly = HDpolly.intersection(MAP)  #exclude map's convex hull and buffer, just the original union of precincts\n",
    "        HDarea[t] = HDpolly.area  #for stats, final Home District area\n",
    "        for nG in range(nGrids) :  # ID the ACTIVE grids to look for intersecting precincts\n",
    "            gridIntersxn = gridGeom[nG].intersection(HDpolly)\n",
    "            if (gridIntersxn.area > 0) :  #this grid is RELEVANT to the final Home District\n",
    "                for tt in range(nGridTracts[nG]):\n",
    "                    nTT = gridTractNo[nG][tt]\n",
    "                    if usedTract[nTT] == 0: #only examine tracts that have not already been called for intersection\n",
    "                        usedTract[nTT] == 1  #this tract has now been called \n",
    "                        overlap = tractGeom[nTT].intersection(HDpolly).area\n",
    "                        if overlap > 0 :\n",
    "                            fracArea = overlap/tractArea[nTT]\n",
    "                            totVAP += fracArea*tractVAP[nTT]\n",
    "                            totHisp += fracArea*tractHisp[nTT]\n",
    "                            totBlack += fracArea*tractBlack[nTT]\n",
    "                        \n",
    "                for pp in range(nGridPrecincts[nG]): #scanning the list of precincts in this active grid\n",
    "                    nPP = gridPrecinctNo[nG][pp]\n",
    "                    if usedPrecinct[nPP] == 0  :\n",
    "                        usedPrecinct[nPP] = 1  #don't double up on precinct intersection\n",
    "                        overlap = vtdGeom[nPP].intersection(HDpolly).area\n",
    "                        if overlap > 0 :\n",
    "                            fracArea = overlap/vtdArea[nPP]\n",
    "                            totGOP += fracArea*vtdGOP[nPP]*vtdPop[nPP]\n",
    "                            totVote += fracArea*vtdPop[nPP]\n",
    "                            loopPrecinctUse[nPP] += overlap/vtdArea[nPP] *tractPop[t]/avgDistrictPop\n",
    "        HDvHisp[t] = totHisp/totVAP\n",
    "        HDvBlack[t] = totBlack/totVAP\n",
    "        HDvGOP[t] = totGOP / totVote\n",
    "        for nPP in range (nPrecincts) :\n",
    "            precinctUse[nPP] += loopPrecinctUse[nPP] #add to global use for this precinct\n",
    "            \n",
    "        \n",
    "\n",
    "    # end of loop on this tract\n",
    "for t in range(nTracts):\n",
    "    if(wrongPop[t] > 0):\n",
    "        HDvPop[t] = wrongPop[t]  #undo the lie that got us out of the loop early\n",
    "HDsumWeight = np.sum(HDweight)\n",
    "print(\"Sum of weights over all precinct home districts should have been 1.000, but was \",HDsumWeight)\n",
    "print(\"Average and max number of wedgePop loops per tract were: \",np.average(tractLoopCounter),np.max(tractLoopCounter) )\n",
    "print(\"min,average,max of Home District areas were: \",np.min(HDarea),np.average(HDarea),np.max(HDarea) )\n",
    "stateGOP2 = 0.\n",
    "stateHisp2 = 0.\n",
    "stateBlack2 = 0.\n",
    "for t in range(nTracts):\n",
    "    HDweight[t] = HDweight[t]/HDsumWeight   #renormalizing\n",
    "    stateGOP2 += HDweight[t]*HDvGOP[t]\n",
    "    stateBlack2 += HDweight[t]*HDvBlack[t]\n",
    "    stateHisp2 += HDweight[t]*HDvHisp[t]\n",
    "statePop = np.sum(tractPop)\n",
    "print(\"calculated statewide vote was {0}, should have been {1}\".format(stateGOP2, stateGOP) )\n",
    "print(\"calcd statewide Hispanic pop was {0}, should have been {1}\".format(stateHisp2, np.sum(tractHisp)/stateVAP ) )\n",
    "print(\"calcd statewide Black pop was {0}, should have been {1}\".format(stateBlack2, np.sum(tractBlack)/stateVAP ) )\n",
    "print(\"fraction of HDs that with altered wedge angles near boundaries = \",np.sum(didWeRestart)/nTracts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "24a347a9-8220-4c1a-bcfc-14923f1f98f7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sum of weights over all precinct home districs should have been 1.000, but was  1.0000466595248172\n",
      "Average and max number of wedgePop loops per tract were:  8.079417241757039 40.0\n",
      "min,average,max of Home District areas were:  0.0 1.0515846864571867 17.000708115617513 for  CA\n"
     ]
    }
   ],
   "source": [
    "#use this line to document progress\n",
    "# start CA HD1 10:00, ends 5:30\n",
    "print(\"Sum of weights over all precinct home districs should have been 1.000, but was \",HDsumWeight)\n",
    "print(\"Average and max number of wedgePop loops per tract were: \",np.average(tractLoopCounter),np.max(tractLoopCounter) )\n",
    "print(\"min,average,max of Home District areas were: \",np.min(HDarea),np.average(HDarea),np.max(HDarea),\"for \",STATE )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "72247942-899a-4ab2-9796-239aa1e524fb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CA 16Mar\n"
     ]
    }
   ],
   "source": [
    "date = \"16Mar\"\n",
    "print(STATE, date)  #check that I will not overwrite existing file :-)\n",
    "tractCPx = [0.]*nTracts\n",
    "tractCPy = [0.]*nTracts\n",
    "tractNo = [0.]*nTracts\n",
    "for t in range(nTracts):\n",
    "    tractCPx[t]=tractGeom[t].centroid.x\n",
    "    tractCPy[t]=tractGeom[t].centroid.y\n",
    "    tractNo[t]=t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "c55ac5fd-7402-47b9-9093-10b9fe0912b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#LET'S WRITE AN OUTPUT FILE BEFORE WE FORGET :-)\n",
    "#convert HD wedge geometries to 1D arrays.  BELOW IS FOR 4-WEDGE.  CAN AUGMENT FOR 6-WEDGE\n",
    "HDangle0 = [0.]*nTracts\n",
    "HDradius0 = [0.]*nTracts\n",
    "HDangle1 = [0.]*nTracts\n",
    "HDradius1 = [0.]*nTracts\n",
    "HDangle2 = [0.]*nTracts\n",
    "HDradius2 = [0.]*nTracts\n",
    "HDangle3 = [0.]*nTracts\n",
    "HDradius3 = [0.]*nTracts\n",
    "for t in range(nTracts):\n",
    "    HDangle0[t] = HDangle[t][0]\n",
    "    HDradius0[t] = HDradius[t][0]\n",
    "    HDangle1[t] = HDangle[t][1]\n",
    "    HDradius1[t] = HDradius[t][1]\n",
    "    HDangle2[t] = HDangle[t][2]\n",
    "    HDradius2[t] = HDradius[t][2]\n",
    "    HDangle3[t] = HDangle[t][3]\n",
    "    HDradius3[t] = HDradius[t][3]\n",
    "# now convert output to pandas dataframe and export\n",
    "\n",
    "paramList = [\"STATE\",\"stateGOP\",\"nDistricts\",\"nTracts\",\"nPrecincts\",\"nWedges\",\"popn-toler\",\n",
    "             \"gain\",\"coeff1\",\"coeff2\"]\n",
    "paramValues = [STATE,stateGOP, nDistricts, nTracts,nPrecincts,nWedges, toler, gain, coeff1,coeff2]\n",
    "for i in range(nTracts-len(paramList)):\n",
    "    paramList.append(\".\")\n",
    "    paramValues.append(-99)  #so all columns have same number of entries, even the parameter list\n",
    "df = pd.DataFrame( {\"paramList\": paramList,\"paramValues\":paramValues,\"HD-pop\":HDvPop,\"HDvGOP\":HDvGOP,\"HDvHisp\":HDvHisp,\n",
    "                    \"HDvBlack\":HDvBlack,\"HDwt\":HDweight,\"HDarea\":HDarea, \"HDangle0\":HDangle0, \"HDangle1\":HDangle1,\n",
    "                    \"HDangle2\":HDangle2,\"HDangle3\":HDangle3,\"HDradius0\":HDradius0,\"HDradius1\":HDradius1,\n",
    "                    \"HDradius2\":HDradius2,\"HDradius3\":HDradius3,\"startAngle\":angle0,\"tractNo\":tractNo,\n",
    "                    \"Loops\":tractLoopCounter,\"tractPop\":tractPop,\"tractHisp\":tractHisp,\"tractBlack\":tractBlack,\n",
    "                    \"centroid x\":tractCPx,\"centroid y\":tractCPy, \"tractUse\":tractUse,\"nearEdge\":nearEdge,\n",
    "                    \"wrongPop\":wrongPop,\"Restart?\":didWeRestart} ) \n",
    "\n",
    "outname = STATE+str(nDistricts)+\"HD1tol\"+str(toler)+\"nW\"+str(nWedges)+date+\".csv\"\n",
    "outpath = \"state_HD_output/\"+outname\n",
    "df.to_csv(outpath)\n",
    "precinctNo = [0.]*nPrecincts\n",
    "vtdX = [0.]*nPrecincts\n",
    "vtdY = [0.]*nPrecincts\n",
    "for p in range(nPrecincts):\n",
    "    precinctNo[p]=p\n",
    "    vtdX[p] = vtdGeom[p].centroid.x\n",
    "    vtdY[p] = vtdGeom[p].centroid.y\n",
    "df2 = pd.DataFrame( {\"precinctNo\":precinctNo,\"precinctPop\":vtdPop,\"precUse\":precinctUse, \"vtdX\":vtdX, \"vtdY\":vtdY} )\n",
    "outname2 = STATE+date+\"_VTD_tol\"+str(toler)+\"nW\"+str(nWedges)+\".csv\"\n",
    "outpath = \"state_HD_output/\"+outname2\n",
    "df2.to_csv(outpath)  #currently, I'm outputting the precinct use stats to a separate file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "c4449da0-47a9-40cc-a585-8288447290e6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "826 0.99 ( -122.08232775101662 37.37876640476918 ) 0.19485998140990768 t, pop/target,(x,y), pctR\n",
      "838 1.15 ( -122.08638127444561 37.36946377434857 ) 0.2032680161863557 t, pop/target,(x,y), pctR\n",
      "3585 1.01 ( -122.84735576228125 38.4144344858161 ) 0.2520953059960872 t, pop/target,(x,y), pctR\n",
      "3959 0.9 ( -116.9805429308055 32.788626080161166 ) 0.4350948808440367 t, pop/target,(x,y), pctR\n",
      "4191 0.96 ( -116.18573321333065 33.68107333686681 ) 0.44865646988408253 t, pop/target,(x,y), pctR\n",
      "8891 0.99 ( -122.4784392460622 37.693289397999266 ) 0.17930691927495068 t, pop/target,(x,y), pctR\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we will redo tract numbers  [838]\n"
     ]
    }
   ],
   "source": [
    "# Looking for nonconvergers ...  Run even if none observed, just to check  \n",
    "redo = [0]\n",
    "counter = 0.\n",
    "for t in range (nTracts) :\n",
    "    if wrongPop[t] > 0 :\n",
    "        ratio = round(wrongPop[t]/avgDistrictPop,2)\n",
    "        tractX = tractGeom[t].centroid.x\n",
    "        tractY = tractGeom[t].centroid.y        \n",
    "        print(t, ratio,\"(\",tractX,tractY,\")\",HDvGOP[t], \"t, pop/target,(x,y), pctR\")\n",
    "        if (ratio < 0.9 or ratio > 1.1) :  #these we will redo\n",
    "            plt.text(tractGeom[t].centroid.x, tractGeom[t].centroid.y,ratio, fontsize=14)\n",
    "            if counter == 0 :  #first redo\n",
    "                redo = [t]\n",
    "            else :\n",
    "                redo.append(t)\n",
    "            counter+= 1\n",
    "        else: #show these milder offenders on the map in a smaller font            \n",
    "            plt.text(tractGeom[t].centroid.x, tractGeom[t].centroid.y,ratio, fontsize=9)\n",
    "\n",
    "x,y = tractMAP.exterior.xy\n",
    "plt.plot(x,y,c=\"purple\")\n",
    "plt.show()\n",
    "print(\"we will redo tract numbers \",redo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "be6e965b-4ca8-4af2-8031-63132fbb939d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "802 0.7848723705873074 618 pop,GOP 0.3284789644012945\n",
      "803 0.7796352144010231 992 pop,GOP 0.33669354838709675\n",
      "814 0.7811215273809949 1026 pop,GOP 0.32456140350877194\n",
      "828 0.7924857997845716 729 pop,GOP 0.32510288065843623\n",
      "846 0.7990412566379791 450 pop,GOP 0.37777777777777777\n",
      "847 0.7965489317451289 464 pop,GOP 0.30387931034482757\n",
      "1816 0.6599505565481525 473 pop,GOP 0.4820295983086681\n",
      "1817 0.6736177987824657 444 pop,GOP 0.4369369369369369\n",
      "1818 0.6087798421715188 867 pop,GOP 0.7151095732410612\n",
      "1819 0.5952759853770646 777 pop,GOP 0.5675675675675675\n",
      "1820 0.5889254732574463 464 pop,GOP 0.4827586206896552\n",
      "1821 0.6438555920410048 426 pop,GOP 0.6830985915492958\n",
      "1822 0.6518168547136058 1000 pop,GOP 0.586\n",
      "1823 0.6026347484325056 1234 pop,GOP 0.6458670988654781\n",
      "1824 0.6014699558214031 398 pop,GOP 0.6231155778894473\n",
      "1825 0.6117187255327362 471 pop,GOP 0.5392781316348195\n",
      "1826 0.6127382723262277 367 pop,GOP 0.4604904632152589\n",
      "1827 0.6143752597807336 353 pop,GOP 0.48158640226628896\n",
      "1828 0.6174204578912313 641 pop,GOP 0.5085803432137286\n",
      "1829 0.6086222537997643 513 pop,GOP 0.5672514619883041\n",
      "1830 0.6387267331530122 716 pop,GOP 0.6480446927374302\n",
      "1831 0.6358827212073093 960 pop,GOP 0.6364583333333333\n",
      "1832 0.662582283755296 633 pop,GOP 0.5244865718799369\n",
      "1833 0.6072106264368213 401 pop,GOP 0.5361596009975063\n",
      "2037 0.7338943189822966 1802 pop,GOP 0.7136514983351832\n",
      "2054 0.7783673484616855 2868 pop,GOP 0.4619944211994421\n",
      "2079 0.729500203853757 4243 pop,GOP 0.5470186189017204\n",
      "2081 0.7248448569315665 3480 pop,GOP 0.49798850574712644\n",
      "2083 0.7216487561757786 4484 pop,GOP 0.493978590544157\n",
      "2085 0.6993492643508009 4204 pop,GOP 0.5456707897240723\n",
      "2087 0.7251020713520102 5199 pop,GOP 0.6008847855356799\n",
      "2089 0.7106386160321752 257 pop,GOP 0.6575875486381323\n",
      "2101 0.7843434669827122 1583 pop,GOP 0.12950094756790903\n",
      "2103 0.7683272926309092 37 pop,GOP 0.4864864864864865\n",
      "2113 0.7193834274421511 3638 pop,GOP 0.6099505222649808\n",
      "2114 0.7849590682981293 4227 pop,GOP 0.491601608705938\n",
      "2115 0.7459815773295353 4038 pop,GOP 0.5346706290242694\n",
      "2121 0.7310859726779145 4 pop,GOP 0.5\n",
      "2122 0.7672097033243992 1056 pop,GOP 0.3001893939393939\n",
      "2128 0.761557217008234 3866 pop,GOP 0.6011381272633213\n",
      "2166 0.7511230690778918 353 pop,GOP 0.3626062322946176\n",
      "2168 0.7982340582807896 1 pop,GOP 0.0\n",
      "2184 0.7523740373078006 1252 pop,GOP 0.11421725239616613\n",
      "2185 0.7405447524466728 1369 pop,GOP 0.17238860482103727\n",
      "2187 0.7764252578654778 263 pop,GOP 0.33840304182509506\n",
      "2200 0.7346807100286732 134 pop,GOP 0.7014925373134329\n",
      "2206 0.7952075740868444 96 pop,GOP 0.3854166666666667\n",
      "2209 0.7069523806057908 3379 pop,GOP 0.5714708493637171\n",
      "2210 0.7496552657622773 1843 pop,GOP 0.4877916440586001\n",
      "2212 0.7976736568767762 1299 pop,GOP 0.2224788298691301\n",
      "2218 0.7959799573444846 1332 pop,GOP 0.2132132132132132\n",
      "2220 0.7930308388462782 1495 pop,GOP 0.2\n",
      "2222 0.7426326563899897 2265 pop,GOP 0.23664459161147902\n",
      "2224 0.770424665056193 1910 pop,GOP 0.2481675392670157\n",
      "2225 0.7785907355361765 724 pop,GOP 0.30386740331491713\n",
      "2232 0.7905944270003482 157 pop,GOP 0.46496815286624205\n",
      "2233 0.7988528396761602 178 pop,GOP 0.3258426966292135\n",
      "2270 0.7794682914948866 27 pop,GOP 0.48148148148148145\n",
      "2271 0.7663050683938637 2 pop,GOP 0.5\n",
      "2281 0.7887860612864737 235 pop,GOP 0.20851063829787234\n",
      "2283 0.7821892998677821 1446 pop,GOP 0.29114799446749656\n",
      "2285 0.773026868644918 964 pop,GOP 0.23236514522821577\n",
      "2291 0.7800124118771163 30 pop,GOP 0.43333333333333335\n",
      "2302 0.7828742659649385 3042 pop,GOP 0.2689020381328074\n",
      "2320 0.7839609791471143 3586 pop,GOP 0.5725041829336308\n",
      "2332 0.7900286148855032 819 pop,GOP 0.2588522588522589\n",
      "2344 0.7841523809694447 3493 pop,GOP 0.6203836243916404\n",
      "2345 0.7941191584704314 3401 pop,GOP 0.5104381064392826\n",
      "2346 0.777431109538386 3125 pop,GOP 0.53312\n",
      "2347 0.7236151002221216 4690 pop,GOP 0.6330490405117271\n",
      "2348 0.7364733950807822 3108 pop,GOP 0.6251608751608752\n",
      "2359 0.7678494481856638 2186 pop,GOP 0.4309240622140897\n",
      "2362 0.7809631610384883 1582 pop,GOP 0.5050568900126422\n",
      "2399 0.7178418680628833 427 pop,GOP 0.765807962529274\n",
      "2414 0.7466639570877337 3965 pop,GOP 0.5778058007566205\n",
      "2501 0.794743241160911 6 pop,GOP 0.8333333333333334\n",
      "2508 0.7043987515938582 17 pop,GOP 0.23529411764705882\n",
      "2509 0.794021440644078 2003 pop,GOP 0.31552670993509735\n",
      "2511 0.7815967182747164 3901 pop,GOP 0.35196103563188924\n",
      "2512 0.7993450152963438 709 pop,GOP 0.28067700987306066\n",
      "2529 0.7527570186561475 155 pop,GOP 0.33548387096774196\n",
      "2532 0.7861013020808147 5 pop,GOP 0.4\n",
      "2534 0.7980058045026832 382 pop,GOP 0.18848167539267016\n",
      "2535 0.7199937972203125 259 pop,GOP 0.17374517374517376\n",
      "2537 0.747389677501399 34 pop,GOP 0.14705882352941177\n",
      "2539 0.7420611085324915 696 pop,GOP 0.21551724137931033\n",
      "2547 0.756588715220662 4671 pop,GOP 0.30357525155213017\n",
      "2548 0.7652375205281239 1577 pop,GOP 0.24159797083069118\n",
      "2549 0.7942237307847919 133 pop,GOP 0.3007518796992481\n",
      "2551 0.7296901053851679 2069 pop,GOP 0.2237796036732721\n",
      "2553 0.7862118271670552 2164 pop,GOP 0.22966728280961182\n",
      "2642 0.7944206286686959 27 pop,GOP 0.37037037037037035\n",
      "2643 0.7907276649366711 10 pop,GOP 0.3\n",
      "2663 0.7720565770907674 92 pop,GOP 0.6521739130434783\n",
      "2676 0.7752999064331962 74 pop,GOP 0.3108108108108108\n",
      "2684 0.7944206286686969 84 pop,GOP 0.30952380952380953\n",
      "2703 0.7910035886671897 1262 pop,GOP 0.2202852614896989\n",
      "2706 0.7813560537053637 892 pop,GOP 0.26681614349775784\n",
      "2708 0.7885291913389197 920 pop,GOP 0.2532608695652174\n",
      "2716 0.7411485760898072 22 pop,GOP 0.7727272727272727\n",
      "2755 0.7958709919276424 192 pop,GOP 0.23958333333333334\n",
      "2786 0.7300537573133138 837 pop,GOP 0.4647550776583035\n",
      "2791 0.7163183548553874 688 pop,GOP 0.5537790697674418\n",
      "2792 0.7552093850011579 849 pop,GOP 0.4994110718492344\n",
      "2793 0.7363909868796121 717 pop,GOP 0.4769874476987448\n",
      "2794 0.7120056156563828 356 pop,GOP 0.47191011235955055\n",
      "2795 0.7417248907684575 677 pop,GOP 0.5568685376661743\n",
      "2798 0.7476002504965952 987 pop,GOP 0.475177304964539\n",
      "2803 0.7822873291082205 531 pop,GOP 0.4331450094161959\n",
      "2804 0.7731227145765917 540 pop,GOP 0.3388888888888889\n",
      "2806 0.7666666370692401 1048 pop,GOP 0.39599236641221375\n",
      "2807 0.770801569894982 568 pop,GOP 0.30809859154929575\n",
      "2808 0.6956205445418208 1116 pop,GOP 0.6594982078853047\n",
      "2811 0.7097462377273579 811 pop,GOP 0.5425400739827374\n",
      "2813 0.7489648704839559 720 pop,GOP 0.40555555555555556\n",
      "2815 0.7320343539627273 582 pop,GOP 0.45532646048109965\n",
      "2816 0.7793635898979011 543 pop,GOP 0.23756906077348067\n",
      "2817 0.7586996066930533 922 pop,GOP 0.42950108459869846\n",
      "2818 0.7950345364978093 193 pop,GOP 0.3160621761658031\n",
      "2821 0.7939082918131584 19 pop,GOP 0.21052631578947367\n",
      "2825 0.75176018878756 77 pop,GOP 0.4675324675324675\n",
      "2835 0.7383465804113339 914 pop,GOP 0.4814004376367615\n",
      "2837 0.7568621734638834 1383 pop,GOP 0.6587129428778019\n",
      "2839 0.7466122926161686 979 pop,GOP 0.4034729315628192\n",
      "2840 0.7457019266852428 1339 pop,GOP 0.8050784167289021\n",
      "2841 0.7186880652352657 63 pop,GOP 0.31746031746031744\n",
      "2842 0.7648232798485316 557 pop,GOP 0.20646319569120286\n",
      "2846 0.7395237187120295 780 pop,GOP 0.5615384615384615\n",
      "2850 0.7451670985448755 713 pop,GOP 0.541374474053296\n",
      "2851 0.7046017010152833 1260 pop,GOP 0.6706349206349206\n",
      "2853 0.7796028222231257 167 pop,GOP 0.2215568862275449\n",
      "2861 0.7464795384108794 1 pop,GOP 0.0\n",
      "2863 0.7236173524145659 485 pop,GOP 0.49896907216494846\n",
      "2864 0.7343894178877732 520 pop,GOP 0.5711538461538461\n",
      "2865 0.721523686134014 768 pop,GOP 0.5859375\n",
      "2880 0.7676634344939838 1214 pop,GOP 0.6771004942339374\n",
      "2885 0.7767621238988474 850 pop,GOP 0.6741176470588235\n",
      "2887 0.7309034110790404 629 pop,GOP 0.6868044515103339\n",
      "2889 0.7352782708213749 1135 pop,GOP 0.6458149779735682\n",
      "2891 0.7037663250366918 656 pop,GOP 0.7621951219512195\n",
      "2896 0.7464568194137656 1399 pop,GOP 0.5303788420300214\n",
      "2903 0.7480308880160014 1027 pop,GOP 0.759493670886076\n",
      "2904 0.7242569621727081 867 pop,GOP 0.8143021914648212\n",
      "2910 0.7334164232667615 11 pop,GOP 0.0\n",
      "2911 0.7570560589443119 1147 pop,GOP 0.7959895379250218\n",
      "2915 0.7345378869584795 977 pop,GOP 0.7697031729785057\n",
      "2916 0.7042420683583402 343 pop,GOP 0.2857142857142857\n",
      "2918 0.6972045070727679 388 pop,GOP 0.3788659793814433\n",
      "2920 0.7678865908179703 759 pop,GOP 0.7760210803689065\n",
      "2922 0.7114201514067512 535 pop,GOP 0.7981308411214953\n",
      "2924 0.7180998912433003 446 pop,GOP 0.30493273542600896\n",
      "2928 0.7305975326612214 716 pop,GOP 0.19134078212290503\n",
      "2933 0.7477456528490702 417 pop,GOP 0.8249400479616307\n",
      "2935 0.7049783166798048 183 pop,GOP 0.22404371584699453\n",
      "2936 0.692643203145463 279 pop,GOP 0.2974910394265233\n",
      "2938 0.7802067325203521 1156 pop,GOP 0.8166089965397924\n",
      "2940 0.7620067386612726 168 pop,GOP 0.6309523809523809\n",
      "2946 0.7701369751618514 851 pop,GOP 0.7896592244418331\n",
      "2959 0.7451633011807007 553 pop,GOP 0.5443037974683544\n",
      "2960 0.7195368974451772 850 pop,GOP 0.5458823529411765\n",
      "2962 0.7515146603575708 442 pop,GOP 0.5927601809954751\n",
      "2963 0.7208953946557048 377 pop,GOP 0.2891246684350133\n",
      "2964 0.7455983674641565 823 pop,GOP 0.5868772782503038\n",
      "2965 0.7397697380167687 1214 pop,GOP 0.6812191103789127\n",
      "2966 0.7560578851515494 817 pop,GOP 0.204406364749082\n",
      "2967 0.7511710479547 451 pop,GOP 0.37472283813747226\n",
      "2968 0.7799539825507807 21 pop,GOP 0.8571428571428571\n",
      "2971 0.7733952757552276 465 pop,GOP 0.7333333333333333\n",
      "2972 0.7879929883496414 840 pop,GOP 0.4119047619047619\n",
      "2974 0.6872039487593494 544 pop,GOP 0.2977941176470588\n",
      "2975 0.793705467979095 843 pop,GOP 0.49110320284697506\n",
      "2982 0.7035322776721238 667 pop,GOP 0.46926536731634183\n",
      "2985 0.731316579214128 4 pop,GOP 1.0\n",
      "2987 0.7424455793845937 607 pop,GOP 0.17957166392092258\n",
      "2995 0.774974654376826 252 pop,GOP 0.44841269841269843\n",
      "2997 0.7901820679523798 495 pop,GOP 0.3515151515151515\n",
      "3000 0.7880111251381589 978 pop,GOP 0.4897750511247444\n",
      "3002 0.7503844519971306 1005 pop,GOP 0.5990049751243781\n",
      "3003 0.7470511192141625 482 pop,GOP 0.7012448132780082\n",
      "3004 0.796539904125323 433 pop,GOP 0.3140877598152425\n",
      "3013 0.7334530269680591 83 pop,GOP 0.2891566265060241\n",
      "3014 0.7747392546431681 40 pop,GOP 0.875\n",
      "3018 0.7768237821615468 2 pop,GOP 0.0\n",
      "3022 0.7316782518757708 448 pop,GOP 0.6004464285714286\n",
      "3036 0.7538459354008161 12 pop,GOP 0.6666666666666666\n",
      "3037 0.7794696108108183 365 pop,GOP 0.6684931506849315\n",
      "3054 0.7815455762506919 45 pop,GOP 0.4444444444444444\n",
      "3055 0.7706422294694772 172 pop,GOP 0.36627906976744184\n",
      "3067 0.71586503916132 58 pop,GOP 0.3620689655172414\n",
      "3072 0.7501068021668401 814 pop,GOP 0.601965601965602\n",
      "3078 0.718174995975182 955 pop,GOP 0.7162303664921466\n",
      "3079 0.7176107034378604 789 pop,GOP 0.4461343472750317\n",
      "3080 0.7438238953377203 1260 pop,GOP 0.4523809523809524\n",
      "3084 0.7275319659280334 517 pop,GOP 0.22243713733075435\n",
      "3090 0.6899754031375025 424 pop,GOP 0.4882075471698113\n",
      "3098 0.7008239764304847 1177 pop,GOP 0.5896346644010195\n",
      "3100 0.7219045260593991 966 pop,GOP 0.5041407867494824\n",
      "3101 0.752678266794377 349 pop,GOP 0.6819484240687679\n",
      "3111 0.7508442542741209 655 pop,GOP 0.3114503816793893\n",
      "3112 0.7410893137568257 820 pop,GOP 0.41341463414634144\n",
      "3118 0.7775183147377184 493 pop,GOP 0.33874239350912777\n",
      "3129 0.7375678458126901 426 pop,GOP 0.5516431924882629\n",
      "3131 0.7213812428059952 1 pop,GOP 1.0\n",
      "3135 0.7634297488242826 332 pop,GOP 0.5240963855421686\n",
      "3137 0.7769086002067287 235 pop,GOP 0.6851063829787234\n",
      "3138 0.7926518232273787 31 pop,GOP 0.6774193548387096\n",
      "3139 0.7612762291923615 2 pop,GOP 0.5\n",
      "3141 0.7227625844228865 721 pop,GOP 0.4812760055478502\n",
      "3144 0.7377311609294248 762 pop,GOP 0.38451443569553806\n",
      "3145 0.7561219714925645 917 pop,GOP 0.6499454743729552\n",
      "3146 0.7174590623166861 624 pop,GOP 0.46794871794871795\n",
      "3148 0.7498173038117053 88 pop,GOP 0.5\n",
      "3150 0.7884149913132025 2 pop,GOP 0.5\n",
      "3154 0.7202847225323601 640 pop,GOP 0.56875\n",
      "3160 0.7048718248539282 265 pop,GOP 0.6\n",
      "3162 0.7155509642650963 842 pop,GOP 0.4489311163895487\n",
      "3165 0.7428639310459292 841 pop,GOP 0.469678953626635\n",
      "3166 0.7073988721262471 550 pop,GOP 0.5\n",
      "3188 0.7858963221391982 15 pop,GOP 0.9333333333333333\n",
      "3192 0.7264687024717448 261 pop,GOP 0.4827586206896552\n",
      "3196 0.7201871385002101 2 pop,GOP 1.0\n",
      "3200 0.7413109915803655 218 pop,GOP 0.5963302752293578\n",
      "3215 0.7758772765846433 1228 pop,GOP 0.7931596091205212\n",
      "3216 0.759991746599835 483 pop,GOP 0.525879917184265\n",
      "3217 0.7843345178391345 834 pop,GOP 0.802158273381295\n",
      "3222 0.7699102457177395 582 pop,GOP 0.46219931271477666\n",
      "3224 0.7821579793250719 219 pop,GOP 0.2191780821917808\n",
      "3225 0.6857214164051986 40 pop,GOP 0.35\n",
      "3231 0.7935395543699164 950 pop,GOP 0.6726315789473685\n",
      "3234 0.7911065845862404 547 pop,GOP 0.4789762340036563\n",
      "3239 0.7468070289369328 632 pop,GOP 0.37183544303797467\n",
      "3242 0.7848038989484396 114 pop,GOP 0.3508771929824561\n",
      "3247 0.7422702560042115 418 pop,GOP 0.47368421052631576\n",
      "3249 0.7621822254198871 76 pop,GOP 0.27631578947368424\n",
      "3251 0.7669279130884944 1017 pop,GOP 0.511307767944936\n",
      "3252 0.7911747353526671 89 pop,GOP 0.14606741573033707\n",
      "3253 0.779900598470869 461 pop,GOP 0.3839479392624729\n",
      "3258 0.760198535321208 107 pop,GOP 0.16822429906542055\n",
      "3259 0.7655570943891288 310 pop,GOP 0.49032258064516127\n",
      "3265 0.7724976196618204 725 pop,GOP 0.4496551724137931\n",
      "3267 0.7847688412703347 14 pop,GOP 0.5714285714285714\n",
      "3285 0.7926134118550484 587 pop,GOP 0.3986371379897785\n",
      "3287 0.7558997373915087 103 pop,GOP 0.2524271844660194\n",
      "3288 0.7885596877518066 730 pop,GOP 0.41506849315068495\n",
      "3291 0.7933504988639678 732 pop,GOP 0.42896174863387976\n",
      "3294 0.7825254332642805 510 pop,GOP 0.40588235294117647\n",
      "3295 0.7456410567304745 544 pop,GOP 0.2665441176470588\n",
      "3296 0.7842594357423222 153 pop,GOP 0.33986928104575165\n",
      "3297 0.788207741635645 878 pop,GOP 0.42369020501138954\n",
      "3304 0.7841637743799198 70 pop,GOP 0.42857142857142855\n",
      "3308 0.7737034731807797 46 pop,GOP 0.2826086956521739\n",
      "3309 0.7500976428971802 901 pop,GOP 0.4483906770255272\n",
      "3315 0.7308906490982552 4 pop,GOP 0.5\n",
      "3316 0.7797011141893653 435 pop,GOP 0.4367816091954023\n",
      "3319 0.7759053497999696 475 pop,GOP 0.4610526315789474\n",
      "3333 0.7828832573128909 582 pop,GOP 0.29037800687285226\n",
      "3349 0.7328408690703446 374 pop,GOP 0.31016042780748665\n",
      "3350 0.7215348189866985 278 pop,GOP 0.2589928057553957\n",
      "3352 0.7262505363743341 379 pop,GOP 0.5145118733509235\n",
      "3353 0.6806049247156636 300 pop,GOP 0.26666666666666666\n",
      "3354 0.713783884965467 181 pop,GOP 0.7182320441988951\n",
      "3356 0.7836741427852938 693 pop,GOP 0.4906204906204906\n",
      "3358 0.7093213594834288 1451 pop,GOP 0.518263266712612\n",
      "3359 0.704799335550772 797 pop,GOP 0.5445420326223338\n",
      "3360 0.7378582050987318 662 pop,GOP 0.5317220543806647\n",
      "3361 0.7021776654452309 1169 pop,GOP 0.6518391787852865\n",
      "3362 0.7697969275683947 30 pop,GOP 0.16666666666666666\n",
      "3363 0.7584489414525536 216 pop,GOP 0.37037037037037035\n",
      "3371 0.7896101434430165 913 pop,GOP 0.5323110624315444\n",
      "3372 0.7936295746658508 1147 pop,GOP 0.5108979947689625\n",
      "3375 0.7787040101507905 773 pop,GOP 0.5860284605433377\n",
      "3376 0.7520995478641964 162 pop,GOP 0.2654320987654321\n",
      "3377 0.7881157118916512 1077 pop,GOP 0.46425255338904364\n",
      "3378 0.7648217642378398 677 pop,GOP 0.40620384047267355\n",
      "3381 0.7544598139293966 674 pop,GOP 0.5593471810089021\n",
      "3387 0.7704002584073555 383 pop,GOP 0.3133159268929504\n",
      "3391 0.7506226633795927 629 pop,GOP 0.465818759936407\n",
      "3392 0.7605555595431892 1071 pop,GOP 0.5275443510737629\n",
      "3396 0.7915338157209352 458 pop,GOP 0.314410480349345\n",
      "3399 0.7873597748149195 1008 pop,GOP 0.39880952380952384\n",
      "3400 0.7772638571477319 833 pop,GOP 0.5762304921968787\n",
      "3401 0.7725173794696581 570 pop,GOP 0.5824561403508772\n",
      "3407 0.7491773530406057 122 pop,GOP 0.5573770491803278\n",
      "3413 0.7954842404729854 822 pop,GOP 0.32116788321167883\n",
      "3419 0.7770905957143139 764 pop,GOP 0.6793193717277487\n",
      "3420 0.7779325041993596 525 pop,GOP 0.29333333333333333\n",
      "3422 0.7196999788219698 1203 pop,GOP 0.5586034912718204\n",
      "3424 0.7084508602645588 1236 pop,GOP 0.6367313915857605\n",
      "3425 0.7260482391334095 944 pop,GOP 0.4841101694915254\n",
      "3427 0.6868391079407139 27 pop,GOP 0.48148148148148145\n",
      "3428 0.7106884350684443 765 pop,GOP 0.49673202614379086\n",
      "3429 0.7689457539003399 267 pop,GOP 0.49063670411985016\n",
      "3430 0.7643057601616912 283 pop,GOP 0.5123674911660777\n",
      "3431 0.7902552507495644 64 pop,GOP 0.4375\n",
      "3433 0.7907159646981541 2 pop,GOP 1.0\n",
      "3434 0.7940796169100766 41 pop,GOP 0.5365853658536586\n",
      "3435 0.7856418123187476 84 pop,GOP 0.40476190476190477\n",
      "3438 0.72540588050796 1068 pop,GOP 0.6601123595505618\n",
      "3439 0.7256119101224622 673 pop,GOP 0.524517087667162\n",
      "3440 0.6837370904138741 19 pop,GOP 0.05263157894736842\n",
      "3441 0.7224599509577072 704 pop,GOP 0.46875\n",
      "3442 0.719176353687837 972 pop,GOP 0.45267489711934156\n",
      "3443 0.7075885566869503 922 pop,GOP 0.40130151843817785\n",
      "3447 0.6994777282300015 436 pop,GOP 0.2706422018348624\n",
      "3448 0.7742773299323167 1693 pop,GOP 0.6952155936207915\n",
      "3449 0.7368509140141217 745 pop,GOP 0.5033557046979866\n",
      "3455 0.7082262802024193 956 pop,GOP 0.5784518828451883\n",
      "3460 0.7755544184702611 948 pop,GOP 0.5316455696202531\n",
      "3461 0.7699762047059988 614 pop,GOP 0.506514657980456\n",
      "3462 0.6878362314776527 478 pop,GOP 0.2615062761506276\n",
      "3466 0.7411647601913899 1155 pop,GOP 0.4623376623376623\n",
      "3467 0.7022790064401524 783 pop,GOP 0.524904214559387\n",
      "3470 0.7029566533615067 824 pop,GOP 0.5133495145631068\n",
      "3689 0.7844547327406813 54 pop,GOP 0.6296296296296297\n",
      "3718 0.7709252020299697 2001 pop,GOP 0.4142928535732134\n",
      "4309 0.7509771374058966 1263 pop,GOP 0.24069675376088678\n",
      "4363 0.7949265098247077 83 pop,GOP 0.6987951807228916\n",
      "4500 0.7861655485608726 2096 pop,GOP 0.31583969465648853\n",
      "4566 0.7727046412307562 1662 pop,GOP 0.3309265944645006\n",
      "4622 0.7787930298314678 1722 pop,GOP 0.3124274099883856\n",
      "4676 0.78200336202634 9 pop,GOP 0.4444444444444444\n",
      "4986 0.7862263277420058 1701 pop,GOP 0.2927689594356261\n",
      "5244 0.7255320565055663 1758 pop,GOP 0.42093287827076226\n",
      "5720 0.7887385939562205 2 pop,GOP 0.0\n",
      "5759 0.7711283672991345 59 pop,GOP 0.711864406779661\n",
      "5824 0.7975761219398485 1746 pop,GOP 0.14375715922107674\n",
      "5962 0.7354007866762429 1786 pop,GOP 0.31746920492721165\n",
      "6095 0.7803751138585239 4 pop,GOP 0.25\n",
      "6200 0.7649721414827239 1645 pop,GOP 0.29908814589665655\n",
      "6530 0.7899189403291601 1641 pop,GOP 0.3753808653260207\n",
      "6574 0.767362149841894 1921 pop,GOP 0.2946382092660073\n",
      "6703 0.7778650326036949 1451 pop,GOP 0.3749138525155066\n",
      "7097 0.7889518473342947 1541 pop,GOP 0.6190785204412719\n",
      "7162 0.2396660689440043 1171 pop,GOP 0.2997438087105038\n",
      "7182 0.17736559863173554 13 pop,GOP 0.38461538461538464\n",
      "7213 0.3935697032482923 142 pop,GOP 0.24647887323943662\n",
      "7234 0.4691717913554826 17 pop,GOP 0.23529411764705882\n",
      "7263 0.4296218603904774 3 pop,GOP 0.3333333333333333\n",
      "7817 0.797852791129606 184 pop,GOP 0.5217391304347826\n",
      "7826 0.7983610623293262 159 pop,GOP 0.49056603773584906\n",
      "7848 0.7463231389679086 56 pop,GOP 0.6785714285714286\n",
      "7934 0.7942834058368532 1435 pop,GOP 0.48362369337979094\n",
      "7994 0.7950215050250585 1043 pop,GOP 0.40364333652924256\n",
      "9435 0.7896985429992637 1573 pop,GOP 0.533375715193897\n",
      "9671 0.7968651043602427 1630 pop,GOP 0.5588957055214724\n",
      "9891 0.7926840060130403 2511 pop,GOP 0.5507765830346476\n",
      "9954 0.7973240789870815 1375 pop,GOP 0.4894545454545455\n",
      "10422 0.7100489200494698 95 pop,GOP 0.17894736842105263\n",
      "10477 0.7671923921335106 1 pop,GOP 1.0\n",
      "10486 0.779784242843332 28 pop,GOP 0.6071428571428571\n",
      "10491 0.756938710375912 14 pop,GOP 0.21428571428571427\n",
      "10494 0.7448402970357092 80 pop,GOP 0.1125\n",
      "10606 0.7418298930682091 536 pop,GOP 0.21828358208955223\n",
      "10634 0.7617308248926461 1253 pop,GOP 0.2673583399840383\n",
      "10644 0.6981893069575288 2 pop,GOP 1.0\n",
      "10666 0.7804651118429737 1798 pop,GOP 0.246384872080089\n",
      "10668 0.7794951025151732 1615 pop,GOP 0.47058823529411764\n",
      "10748 0.771968779868833 2100 pop,GOP 0.4533333333333333\n",
      "10749 0.776954298624604 1009 pop,GOP 0.4697720515361744\n",
      "10762 0.7358366358858294 2566 pop,GOP 0.4142634450506625\n",
      "10767 0.7945255787004392 86 pop,GOP 0.20930232558139536\n",
      "10793 0.7332104298303258 1491 pop,GOP 0.24413145539906103\n",
      "10879 0.7833844972310372 1493 pop,GOP 0.6001339584728734\n",
      "10925 0.7800145251790931 3056 pop,GOP 0.45287958115183247\n",
      "10927 0.7976075664485953 5152 pop,GOP 0.31618788819875776\n",
      "11037 0.7337050056199467 2653 pop,GOP 0.19449679607990952\n",
      "11046 0.6857593911362272 1566 pop,GOP 0.46424010217113665\n",
      "11051 0.6783388170131057 88 pop,GOP 0.38636363636363635\n",
      "11103 0.7977434645125647 3715 pop,GOP 0.5755047106325707\n",
      "11117 0.7090989907764095 7214 pop,GOP 0.2019683947879124\n",
      "11125 0.7929378394480973 287 pop,GOP 0.46689895470383275\n",
      "11155 0.7386446086876386 1 pop,GOP 1.0\n",
      "11156 0.7992804957673931 1428 pop,GOP 0.14285714285714285\n",
      "11158 0.6931180749074285 2 pop,GOP 0.5\n",
      "11168 0.7675088985376213 1369 pop,GOP 0.28195763330898466\n",
      "11169 0.7399481754463154 8 pop,GOP 0.625\n",
      "11173 0.7217043800946751 14 pop,GOP 0.5714285714285714\n",
      "11176 0.7514927600249195 111 pop,GOP 0.8738738738738738\n",
      "11178 0.7219406769955048 66 pop,GOP 0.7272727272727273\n",
      "11596 0.7972703716052452 1107 pop,GOP 0.17524841915085818\n",
      "11602 0.7963643870848094 965 pop,GOP 0.21347150259067357\n",
      "11605 0.7862888930612748 261 pop,GOP 0.2950191570881226\n",
      "11940 0.7987909040212368 1780 pop,GOP 0.3219101123595506\n",
      "11948 0.7897225359169162 849 pop,GOP 0.2661955241460542\n",
      "12427 0.7980052245657934 5 pop,GOP 1.0\n",
      "12939 0.7882078742074523 381 pop,GOP 0.4304461942257218\n",
      "12967 0.7930364950359201 4 pop,GOP 1.0\n",
      "13321 0.7978881639497716 480 pop,GOP 0.23958333333333334\n",
      "13353 0.7994438213951653 21 pop,GOP 0.8095238095238095\n",
      "13467 0.7956387993636298 243 pop,GOP 0.38271604938271603\n",
      "14153 0.7977109673213999 2 pop,GOP 1.0\n",
      "14536 0.7870567776200998 7470 pop,GOP 0.2175368139223561\n",
      "14602 0.7049883632938202 2654 pop,GOP 0.2584777694046722\n",
      "14604 0.7987578592546523 5523 pop,GOP 0.2866195908021003\n",
      "14606 0.7921021018716145 4358 pop,GOP 0.3187241854061496\n",
      "14607 0.7201795739373933 5208 pop,GOP 0.24097542242703532\n",
      "14608 0.6930215864143672 5327 pop,GOP 0.31762718227895625\n",
      "14609 0.7523299315217432 909 pop,GOP 0.24532453245324531\n",
      "14610 0.7813730442506691 2501 pop,GOP 0.34986005597760894\n",
      "15422 0.7547154936353765 205 pop,GOP 0.4097560975609756\n",
      "15445 0.6697141442624547 96 pop,GOP 0.3020833333333333\n",
      "15453 0.7711421944763227 7 pop,GOP 0.2857142857142857\n",
      "15580 0.7680074065800354 2 pop,GOP 1.0\n",
      "15728 0.791759037332769 689 pop,GOP 0.09724238026124818\n",
      "15729 0.7964214922037726 629 pop,GOP 0.12559618441971382\n",
      "15730 0.7908795626163607 675 pop,GOP 0.06074074074074074\n",
      "15767 0.7783122404221863 889 pop,GOP 0.12148481439820022\n",
      "15773 0.7980003045945314 794 pop,GOP 0.163727959697733\n",
      "15774 0.7897078376933642 935 pop,GOP 0.15401069518716579\n",
      "15775 0.7906537927067084 775 pop,GOP 0.16\n",
      "15801 0.7712708216103471 896 pop,GOP 0.10267857142857142\n",
      "15894 0.7942145201674411 604 pop,GOP 0.12582781456953643\n",
      "16464 0.10399863298420611 875 pop,GOP 0.24914285714285714\n",
      "16481 0.5067103037321744 495 pop,GOP 0.1292929292929293\n",
      "16483 0.7991929389648197 209 pop,GOP 0.15311004784688995\n",
      "16501 0.17940296475702014 99 pop,GOP 0.3333333333333333\n",
      "16504 0.1714675002884942 844 pop,GOP 0.20023696682464456\n",
      "16539 0.5508971860451359 610 pop,GOP 0.10819672131147541\n",
      "16570 0.5440771514785594 2700 pop,GOP 0.2174074074074074\n",
      "16596 0.7919969924789476 2336 pop,GOP 0.16909246575342465\n",
      "16964 0.7907620624050565 2418 pop,GOP 0.2109181141439206\n",
      "16990 0.7942928295597098 3023 pop,GOP 0.2593450215018194\n",
      "17201 0.7852992677316042 3160 pop,GOP 0.3392405063291139\n",
      "17210 0.7971440252046295 3103 pop,GOP 0.308733483725427\n",
      "17211 0.7974549455067516 3874 pop,GOP 0.3425400103252452\n",
      "18077 0.6879635943491995 893 pop,GOP 0.6114221724524076\n",
      "18079 0.7904101375196924 2180 pop,GOP 0.6674311926605505\n",
      "18084 0.696187629676847 623 pop,GOP 0.6276083467094703\n",
      "18091 0.7445726454986834 326 pop,GOP 0.6134969325153374\n",
      "18102 0.6936515809553937 446 pop,GOP 0.6659192825112108\n",
      "18114 0.6785423632888115 102 pop,GOP 0.7156862745098039\n",
      "18118 0.7115522940221242 2572 pop,GOP 0.7177293934681181\n",
      "18121 0.7832588602901039 1663 pop,GOP 0.6361996392062538\n",
      "18124 0.6580321452307933 6 pop,GOP 1.0\n",
      "18125 0.6835640307380417 9 pop,GOP 0.3333333333333333\n",
      "18127 0.7661137177212098 1133 pop,GOP 0.6954986760812003\n",
      "18129 0.6679413556737989 982 pop,GOP 0.7026476578411406\n",
      "18130 0.6612295341457903 236 pop,GOP 0.6059322033898306\n",
      "18133 0.6485378040231379 152 pop,GOP 0.46710526315789475\n",
      "18134 0.7791160404280443 1409 pop,GOP 0.5855216465578424\n",
      "18135 0.6852175501031583 79 pop,GOP 0.379746835443038\n",
      "18138 0.6753331049079034 1280 pop,GOP 0.71875\n",
      "18142 0.680706328001211 194 pop,GOP 0.654639175257732\n",
      "18146 0.7290240111526362 1713 pop,GOP 0.7472270869819031\n",
      "18147 0.727319457869585 2012 pop,GOP 0.643141153081511\n",
      "18149 0.6617523239458784 1990 pop,GOP 0.6572864321608041\n",
      "18150 0.6592691284830811 690 pop,GOP 0.636231884057971\n",
      "18151 0.7171528999124379 1982 pop,GOP 0.6321897073662966\n",
      "18152 0.7933273828601245 832 pop,GOP 0.5228365384615384\n",
      "18154 0.6677990951179387 76 pop,GOP 0.8947368421052632\n",
      "18155 0.6611953560593683 2664 pop,GOP 0.6482732732732732\n",
      "18159 0.7797983036589362 60 pop,GOP 0.6\n",
      "18160 0.7926115133167941 1410 pop,GOP 0.7489361702127659\n",
      "18166 0.718360439031276 1775 pop,GOP 0.704225352112676\n",
      "18167 0.686673010981899 1301 pop,GOP 0.7401998462720983\n",
      "18168 0.7935941910614001 264 pop,GOP 0.5984848484848485\n",
      "18192 0.6169124606460242 192 pop,GOP 0.7864583333333334\n",
      "18193 0.6363590114719663 722 pop,GOP 0.4002770083102493\n",
      "18194 0.6081163988779987 639 pop,GOP 0.7339593114241002\n",
      "18195 0.6478356768913371 134 pop,GOP 0.6119402985074627\n",
      "18196 0.6817486173184099 2 pop,GOP 1.0\n",
      "18197 0.6529836120406847 173 pop,GOP 0.45664739884393063\n",
      "18198 0.6387356260219692 611 pop,GOP 0.32569558101472995\n",
      "18199 0.631684308090614 225 pop,GOP 0.5288888888888889\n",
      "18200 0.6019653754866273 249 pop,GOP 0.7951807228915663\n",
      "18201 0.6158728756421724 427 pop,GOP 0.6814988290398126\n",
      "18202 0.6032673496381391 253 pop,GOP 0.7312252964426877\n",
      "18203 0.6169932054407588 126 pop,GOP 0.746031746031746\n",
      "18204 0.6109330086126148 169 pop,GOP 0.7218934911242604\n",
      "18205 0.6463733021516467 572 pop,GOP 0.5996503496503497\n",
      "18206 0.6189905249756885 152 pop,GOP 0.6776315789473685\n",
      "18207 0.6178926181045007 62 pop,GOP 0.7419354838709677\n",
      "18208 0.630608313457293 152 pop,GOP 0.5986842105263158\n",
      "18209 0.6188960832014813 677 pop,GOP 0.7680945347119645\n",
      "18210 0.6733635670132757 53 pop,GOP 0.24528301886792453\n",
      "18211 0.73763105956915 141 pop,GOP 0.8226950354609929\n",
      "18212 0.695485421517105 275 pop,GOP 0.6763636363636364\n",
      "18213 0.6242570580459426 581 pop,GOP 0.49569707401032703\n",
      "18214 0.6576584007636345 747 pop,GOP 0.6813922356091031\n",
      "18215 0.7478386998754897 179 pop,GOP 0.6089385474860335\n",
      "18217 0.6452803347802886 826 pop,GOP 0.3801452784503632\n",
      "18218 0.6184938286052403 618 pop,GOP 0.6116504854368932\n",
      "18220 0.6250414860659915 263 pop,GOP 0.6692015209125475\n",
      "18221 0.6295513846525576 210 pop,GOP 0.7333333333333333\n",
      "18222 0.609592776658054 627 pop,GOP 0.5901116427432217\n",
      "18223 0.6168951178023817 633 pop,GOP 0.608214849921011\n",
      "18224 0.6489080108394996 806 pop,GOP 0.6823821339950372\n",
      "18225 0.6189235303119835 423 pop,GOP 0.5957446808510638\n",
      "18227 0.6293319702987613 207 pop,GOP 0.8019323671497585\n",
      "18228 0.6407161577200372 487 pop,GOP 0.6981519507186859\n",
      "18230 0.6223721075045057 23 pop,GOP 0.5652173913043478\n",
      "18231 0.6140782441061217 61 pop,GOP 0.7704918032786885\n",
      "18232 0.6162633672205079 200 pop,GOP 0.795\n",
      "18233 0.6992907847443162 202 pop,GOP 0.7326732673267327\n",
      "18234 0.6192057804243317 652 pop,GOP 0.6395705521472392\n",
      "18235 0.6877593681460812 168 pop,GOP 0.7916666666666666\n",
      "18236 0.6167631264951025 10 pop,GOP 0.9\n",
      "18237 0.6419276758939915 2 pop,GOP 0.5\n",
      "18238 0.6296863946760048 758 pop,GOP 0.4393139841688654\n",
      "18239 0.6393108065066603 505 pop,GOP 0.3702970297029703\n",
      "18240 0.6133866809740174 105 pop,GOP 0.4\n",
      "18241 0.608501487945413 148 pop,GOP 0.6621621621621622\n",
      "18242 0.6515325501012719 357 pop,GOP 0.6610644257703081\n",
      "18243 0.6267075808266183 859 pop,GOP 0.5087310826542492\n",
      "18244 0.6831802030102373 199 pop,GOP 0.5728643216080402\n",
      "18245 0.6255942243334915 289 pop,GOP 0.4359861591695502\n",
      "18246 0.6400416753590369 345 pop,GOP 0.6405797101449275\n",
      "18247 0.6147761911814416 329 pop,GOP 0.7386018237082067\n",
      "18248 0.62186201715009 20 pop,GOP 0.25\n",
      "18249 0.6258193780102419 455 pop,GOP 0.4153846153846154\n",
      "18250 0.6426760635628386 320 pop,GOP 0.628125\n",
      "18251 0.6366353755168465 624 pop,GOP 0.3573717948717949\n",
      "18252 0.624835767023388 218 pop,GOP 0.6972477064220184\n",
      "18253 0.6241130594801149 281 pop,GOP 0.6583629893238434\n",
      "18254 0.6146709752194526 527 pop,GOP 0.6660341555977229\n",
      "18255 0.6204609743923526 516 pop,GOP 0.49224806201550386\n",
      "18256 0.6249856878565216 915 pop,GOP 0.5409836065573771\n",
      "18257 0.6217515417614417 445 pop,GOP 0.4943820224719101\n",
      "18258 0.6253916954392786 513 pop,GOP 0.4834307992202729\n",
      "18259 0.6403799414743451 224 pop,GOP 0.5089285714285714\n",
      "19355 0.7516011308319392 188 pop,GOP 0.3776595744680851\n",
      "19356 0.7858193402305518 1458 pop,GOP 0.25102880658436216\n",
      "19360 0.7660722504653518 2959 pop,GOP 0.4082460290638729\n",
      "19362 0.7968284820288517 2291 pop,GOP 0.40549978175469226\n",
      "19366 0.7892388553619339 733 pop,GOP 0.4311050477489768\n",
      "19371 0.7836503730046865 228 pop,GOP 0.5087719298245614\n",
      "19372 0.7499417632421526 543 pop,GOP 0.36095764272559855\n",
      "19375 0.7824460899588866 388 pop,GOP 0.4639175257731959\n",
      "19391 0.7399807744210366 982 pop,GOP 0.3788187372708758\n",
      "19392 0.7579007851039747 1466 pop,GOP 0.5190995907230559\n",
      "19402 0.7683315762921119 2487 pop,GOP 0.45757941294732607\n",
      "19403 0.7565715333897406 321 pop,GOP 0.3956386292834891\n",
      "19406 0.7689753948757702 5854 pop,GOP 0.4750597881790229\n",
      "19412 0.7672733581642204 1805 pop,GOP 0.4421052631578947\n",
      "19413 0.7561300136985187 1135 pop,GOP 0.5233480176211454\n",
      "19414 0.797704116902233 1281 pop,GOP 0.2029664324746292\n",
      "19415 0.7678713812441357 817 pop,GOP 0.48592411260709917\n",
      "19416 0.760907112157174 883 pop,GOP 0.3669309173272933\n",
      "19417 0.787596187465144 807 pop,GOP 0.483271375464684\n",
      "19420 0.7833205599795511 1628 pop,GOP 0.5442260442260443\n",
      "19422 0.7543446700571469 2259 pop,GOP 0.4864984506418769\n",
      "19432 0.7685336016997887 1636 pop,GOP 0.48594132029339854\n",
      "19435 0.7548972165548031 4592 pop,GOP 0.46668118466898956\n",
      "19436 0.7779641154241534 482 pop,GOP 0.4170124481327801\n",
      "19437 0.7707580672650377 348 pop,GOP 0.47701149425287354\n",
      "19488 0.7456477908513578 74 pop,GOP 0.40540540540540543\n",
      "19517 0.7844929114010071 123 pop,GOP 0.6178861788617886\n",
      "19519 0.7886646184996697 14 pop,GOP 0.42857142857142855\n",
      "19523 0.7801920872281323 81 pop,GOP 0.48148148148148145\n",
      "19527 0.7953449029056281 170 pop,GOP 0.34705882352941175\n",
      "19543 0.7952271754078473 12 pop,GOP 0.75\n",
      "19643 0.7287611391278783 317 pop,GOP 0.555205047318612\n",
      "19645 0.7807730048708634 85 pop,GOP 0.4823529411764706\n",
      "19646 0.7004743265083729 688 pop,GOP 0.5537790697674418\n",
      "19650 0.7775659842357601 529 pop,GOP 0.4763705103969754\n",
      "19651 0.768883072510306 16 pop,GOP 0.375\n",
      "19652 0.6408818461994767 128 pop,GOP 0.4375\n",
      "19653 0.6501113145420657 180 pop,GOP 0.8\n",
      "19654 0.7068859130035998 335 pop,GOP 0.42686567164179107\n",
      "19655 0.6636589119924958 82 pop,GOP 0.5853658536585366\n",
      "19656 0.748755576673672 402 pop,GOP 0.6218905472636815\n",
      "19657 0.7414748455786377 874 pop,GOP 0.5160183066361556\n",
      "19658 0.7789102539768666 86 pop,GOP 0.4883720930232558\n",
      "19659 0.7592679656977533 352 pop,GOP 0.38636363636363635\n",
      "19660 0.789526240818015 168 pop,GOP 0.4880952380952381\n",
      "19667 0.7760740011410694 63 pop,GOP 0.7301587301587301\n",
      "19676 0.7999857251304567 196 pop,GOP 0.6479591836734694\n",
      "19680 0.7779389789416356 8239 pop,GOP 0.5857506979002306\n",
      "19684 0.7488219654916267 83 pop,GOP 0.30120481927710846\n",
      "19685 0.75713015114605 3910 pop,GOP 0.5051150895140665\n",
      "19686 0.7624136433563266 431 pop,GOP 0.5452436194895591\n",
      "19731 0.7768400686406284 3636 pop,GOP 0.6009350935093509\n",
      "19732 0.7806688385779607 1300 pop,GOP 0.5169230769230769\n",
      "19734 0.7750146605186693 1706 pop,GOP 0.4847596717467761\n",
      "19740 0.7392965097417528 879 pop,GOP 0.24800910125142206\n",
      "19741 0.7707634567791432 800 pop,GOP 0.42625\n",
      "19742 0.7483375765453882 876 pop,GOP 0.3139269406392694\n",
      "19763 0.7290063967900456 1122 pop,GOP 0.3048128342245989\n",
      "19764 0.7253441322396132 538 pop,GOP 0.4739776951672863\n",
      "19768 0.7569278690083573 278 pop,GOP 0.49280575539568344\n",
      "19770 0.7848225414614117 369 pop,GOP 0.5392953929539296\n",
      "19773 0.7265905572182811 244 pop,GOP 0.3729508196721312\n",
      "19774 0.7547123818271586 156 pop,GOP 0.5\n",
      "19775 0.7659398625739117 22 pop,GOP 0.4090909090909091\n",
      "19792 0.7723135562298136 20 pop,GOP 0.8\n",
      "19796 0.749477457150713 149 pop,GOP 0.9060402684563759\n",
      "19797 0.7834453638561252 30 pop,GOP 0.6\n",
      "19805 0.7804223999055886 358 pop,GOP 0.2011173184357542\n",
      "19806 0.7567570673271045 761 pop,GOP 0.6898817345597897\n",
      "19814 0.7490826244590791 581 pop,GOP 0.3098106712564544\n",
      "19815 0.7420553320418272 247 pop,GOP 0.3117408906882591\n",
      "19816 0.7492080983462542 234 pop,GOP 0.7564102564102564\n",
      "19818 0.7347467241177796 42 pop,GOP 0.6666666666666666\n",
      "19819 0.7471352509818626 18 pop,GOP 0.7222222222222222\n",
      "19820 0.750654722792628 362 pop,GOP 0.7569060773480663\n",
      "19839 0.7921873464316235 7 pop,GOP 0.5714285714285714\n",
      "19876 0.796813029710871 1152 pop,GOP 0.6302083333333334\n",
      "19910 0.7354079329524833 96 pop,GOP 0.25\n",
      "20186 0.7250314241540939 205 pop,GOP 0.5560975609756098\n",
      "20198 0.5873119759805943 7 pop,GOP 0.2857142857142857\n",
      "20202 0.6311522054555501 407 pop,GOP 0.21375921375921375\n",
      "20203 0.6463713584668656 606 pop,GOP 0.2953795379537954\n",
      "20206 0.6557276111625958 2094 pop,GOP 0.30945558739255014\n",
      "20284 0.7810491511031478 458 pop,GOP 0.25327510917030566\n",
      "20362 0.6757165876109895 51 pop,GOP 0.13725490196078433\n",
      "20472 0.6901186544373119 579 pop,GOP 0.23316062176165803\n",
      "20484 0.7411907287653229 1027 pop,GOP 0.317429406037001\n",
      "20485 0.7358878975686631 1317 pop,GOP 0.18906605922551253\n",
      "20489 0.7746237088852028 181 pop,GOP 0.20441988950276244\n",
      "20509 0.7867579890479967 1018 pop,GOP 0.24263261296660119\n",
      "20513 0.5979202549928848 1 pop,GOP 0.0\n",
      "20521 0.6615475173039588 402 pop,GOP 0.26616915422885573\n",
      "20536 0.6864941358237728 1120 pop,GOP 0.2669642857142857\n",
      "20539 0.6959665008643983 366 pop,GOP 0.1830601092896175\n",
      "20552 0.7716846603575368 1064 pop,GOP 0.18233082706766918\n",
      "20574 0.7519214395802913 1419 pop,GOP 0.4080338266384778\n",
      "20607 0.580201201655714 1010 pop,GOP 0.33564356435643566\n",
      "20627 0.7253861997130736 1291 pop,GOP 0.27420604182804026\n",
      "20638 0.5901560516409512 256 pop,GOP 0.390625\n"
     ]
    },
    {
     "data": {
      "image/png": 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sVH24Ku2nv4J//Xn4A20827A8fTmpq1OxrbHx9U9f03pAa6o+VpVjO47h5uPG2RNnyTqbxaFULYqrG20nvs+kLj145MGH2bdtOzofb/LqNsYrLQmTZLFgxkKMZiNpthxS0zNoXjmY2P1pPFjFRG6BjUA3hdijp9EYtQSatXhl5jJ1hx1Pk4HElZtIOZtFj4fa8PvclRTkF+Lj7kl8WwuWE+XQbNl0sb9e4aaOOuvUqcO2bduKlWXl2cgwKDQJcSGmgoMtuw/TBti0aRNHjx7lm2++oVq1aixatIiCggIefPBBOnYsemjZrVs3unXrRlJSEv369bupUUnXgqg+chUVoJQJ+QV0Jh21+9amdt/a5KXlMb39dOLnx9PqaCseL/84Px/5mRWpKxCN4NXcC5oXnbeXvUUvWsKxXcfIzsjG95k2eAW8wrmnHmHuo09hNBrZGLuKnj178kD3LgyOTyFt1TI2nkvFd+kWzj31CI/WqcLkRUup4uXKRq2R1MIgjmam0jTCi+92HMJkCaQgA8btiWD9qbUYtFqWbvoLd5ORBYs34OruQUZaOpnZ2bQ+1pS49P2YTKZiE49uBaNHj6ZTp6L4drv97/DKGk074edppm/IYp7acZKWLVsSHx/PoEGDaNOmDePGjWPevHkAjBgxAj+/ooVK+vTpw4kTJ3BxcWHChAm31PZiqANyFZVilEoh/ydmLzPdZ3ZnfKXxrP1gLS9+/SK5q3IRhCEvDsGBAy8XL3RaHYqiICJ89913fLn6S87uO0v1Lq1ZRRKK2YVjOXnM//xz5s6dS2JiIosXL6bbw91Ysn8H9RrU59j/9Sf7zCmWrsukiY83ZTy8qVuuHFtPnmLrySQOnEkjr8DBgdOpKBotbvWb0ulsMmv2HyPHWoiPqwvtwsNYcDCBNARPs4XypgD2WY+gQUdlv0p4lnHjr93bQUCr0WG3X68X/PJcEPF/s2DBAgCM9XVUiw5m1W9r0el0NG7cGIAqVarw008/YTKZmDFjBu3ateP06dMcP34cu91Oeno66enpN83Oa0YdkKuoAHdJ9kOvil7Ufaou27/bzpElR2jTpg0KCplnM/F390ev0zv9qunp6UycOJF169bx5ptvsuS14djeGYHbcy/RdNZC8qxWYmNj2bVrF2azmbjNcbhaXIldtpKC/AJiV8ayJ+UcSloWjSJq8vp9D5BpLcTDZMbP1Z0+DaJo7qagt2fw4ptvsXHvDj5o44JeY+dsVjZLDx0iPy8HESGrIJeZe36h3ftvYNNrOZR2nO3x+1C0RbZ6m42XHXyadC5XvCd1y3pc9pjRaCQyMtK5bzabURSFJYftbNx5kOPHj3Pq1Cnatm2Lm5sbDz/8MCNHjmTNmjXo9XqWLl3KtGnTKCgoQKvVcvToUbp27Vqsj39nQkxISKBz5860atWKPn36XNH2q6H6yFVUilPqR+QX6DSxE0dXHiV2ZCw9lvYgb9kYDN//RJKYOZAfw56MohSse0/8hYe9AlNeXYqHtgblypYjbusW/rd1NxOtOr5auJ8FTZpgs9kwGAzM/30ue/o/xYCEI7TIzuGp1q3xU2B1djavf/Qhj3t5E5GXTxsXM3+mpnFq124SHPks7Wfm0V8K2H+ukPHrTvNCk0CeOGqnWw1f1sRnkW1N4at20dhFQ9XsHCY77FSpWpN+jT/knV96Y5VcGodWYsmO3eTbCy+63svN7LzA1lMZxfY1Gg3uHm6kp2VgtVo5ceK481heXh56vZ7ErEJy9xyicePGlCtXjj179pCdnU29evV444036NSpExkZGfj5+fH666/z+uuvA0Winf2Ph7Xz58/H3b34VPzBgwfzzTffEBgYeH1v7BVQfeQqKkXcFUKecTyDnTN2knqoKPzNYrTQ3OUwxtzTWDGzdfefTIxbioJC1fINMevdwa7FnmMgNTWdFs1bcNJaSMrpJLBa2X74OPd1akNSYhJt27el4ZlkEAdtW7ejpcHIiv17mbtzG71ff4Opixbx1quv8NGMGbidOEHamSSiPFxwaTqS+a/3pF3NQD7vZGTIVh8eeTSGT6bPABEqGAyMX7ERk6JQ/Www9gLYuXsHw/fej0OsjHjZj+PHqqLs2w95Fwu51XZxaOSVcDgcpKf9Le65uX+frwCFhYXYFcjKzyE4OJi1a9ei1+upXr06gwYNokOHDkRGRlK7dm3q1/875cPp06eJi4vj999/d/bz+eefM3ToUGbPng3AsWPHyM3NZejQoSQnJzNkyBC6det2XfYXQx2Qq6gUo9S7Vk5vP80X1b5gxWsrcC3jSljHMLTWsxhzk6Dde5zKL8PUbUnsP76NZRvmsfPkKvKs2UR3iwBAazfTs9Yo7J9+i8bLG32d+lTbeYhNx05gBc4UONiYm4Pdbsdv9y4enPgJCUYdZzIzefXHGfy+fh0/7d3L9pMnqd6wIdvz8lh8JpsvPv4Kx5v9MGu9+HRTWbbv2MvWX2cTrNPT28ubDc8/SM9HOlI5uh6LEmJ54ZkGuFi0OLDRMMqP1q1dKVu2LIqioNVqi12zQtE0++vBZLx8vLpzXKtAntXB//73PwwGA8eOHaNNmzY888wzlC9fHnd3d1avXs2HH37oPPfBBx8kODiY9957j5iYGPz9/bHZbJhMJk6cOEFUVBRdunRh/fr1jB07lrlz5/L222+TkJBw4wtzqANyFRXgLhiR75m1h4LsAgZsHEDZBmXPF/7G1O0FfD1/CueOHaBqkDcGg4HQ0FAURWFbwmoGjnictHMZJGccZ+Wx7+h/oA8fHjmM4VwqticfRjmXglf5inxakMtzhYVEubhwNOkk9QttHDlyhAEDBtCgQQNefPFF/vjjD7Kyspg9ezbh7hbqKnpW7TlB4+QCzp3NYmbiOSaUDaaRxUKjg/F0/r+B+L3yHi3nf8/kYU9Tr5mR72bHMunrIN584zSuHgX8+mVzmrc5g9HNSF6Bvegr11EUaSJAgE7H6cKikbr2fJmi0WA/H8Ko0WiKhTMWFAr+AQGcOXOm6BytFr1ej91ux2w2k5mZicMBHh6uLJnzC9lZWWi1Wl599VXKlCnD6dOnsdvtaLVaRo4cic1mIz09nePHjxMbG0t4eDj5+fkEBwfz9ttvY7PZiIuLIy4ujvz8fJo3b87evXvp2LEjtWvX5q233iI6Ovo/veeqj1xFpTilfkQe1iEMjU7DlIZT+O3x3wBI2z6f8Zts9Ht6EHmFDhbsOe1c8s2AhdY1u3P40FESk09gdjGzftsKZo59nk7t29Gv1yO0blgXsdvIOp7AS6eTEOCoi4Wnk1Pw8/fjwIED9OvXj/vuuw8/Pz9CQ0N59tlnsVgs1LmvK3tDK9Js6Ats79+PDA8PyoaG0v3PXwkY+yqefr78dXgHa2fW4Le/RuDmqcHb7o5BXClfYRgWiwaLxcFp407mmLfg4uVAb9JT+7He6PUaLmjY6cJC3M7v2AG9otAqpIzzvjgcDtzc3Jyi53A4nCIOYDKZcDgcFBYWkpmZiU6nAz1kpWXyzIsvkZGehsNuR6PRUKVKFex2O2fOnMHT0xONRsPs2bP53//+R0pKCk899RQPPfQQDz/8MGlpaXTp0oUXX3yRvLw8Pv74Y4YPH865c+f49NNPsdlsbN++nby8vGIumv+C6iNXUTnPlebv3+ztVq0QdHz9cRnJSPlfmf+JpJ+QP3u7ydPtq0udOnXk2SgP0SqIyWSSkLLhYtCZZPgD42XtL/EyatQocXFxEbPZLIqiiI+np+h1OgkpV64oJ4tWK+6KIlqQWtVrSkREhDP/Su3atSU8PFwiIiKkXr16EhkZKRqNRvR6vVgsFtHr9eLu7i4dWjYVPy9X0WgUcTHpZHAff2nT1lVq1TRJo5r+0rtrjAQGBkpkZKSEhriKyaRIw4ZmmTc/RGbOLC8mkyJ6fVF+Fo0GCQzUyfnZ/VLTZBINiI+3t2jP523R6/Xi5eUler1eDAaDM28M5/Os6PV6cXFxkb59+4pOp3NeZ1h4JUFBmrSvVZQHRinKDwOIq6urPPXUU+Lp6Sl6vV40Go0sWbJEwsLCZNiwYfL+++9LmTJlxN/fX9q2bSsiIitXrpSOHTs6VyRq3ry5REdHS4MGDaRx48ayd+9eefvtt+WHH3647vc752yOjGSk/DX+r5v9UVJRuSPhFuZauSM4tekUMx+YCUCz15vCivdIzXOQ4x6Gu7s738RlYBfIz8/Hmm8lwLM8i/dNZePxeYwfPx6bzUZeXh4iQohPHXQaI0dPnACKJs24u3ujKBoO748nPj6e/Lx8APbs2YOXlxfz589ny5Yt7N+/nylTpuDv74/ZbKZGWFmyszOJ3bCOzNxsmjQxU7WGngWr0njz0R6snreOhbH72ZmQSpkyZZg7dy4uFjOVwgyMfj8Qs1lDQkIBNWqY6POEN0uXVaRjJzeyshxcmMuzO7/IFsnIIMbVlc7u7igGB2mZaRQ6CimUQjTuGip9GoLGoin6/eUu5Nnz+HnFTPQhOhSdgt1u59ChwygmhRPBZ3Gv447WXYeLtxGNRkN0dDR5eXmsW7eOnJwctFotgwcPRqfTMWrUKL799lvn9PzVq1fz6quvEhMTw549e6hbty716tXj4MGDNGzYkClTplC1alWqVKly42++OiBXUQHuAh/5sleWodFp6LeuH+UOD4Udy/Gu0Y6k1Rls3rwZh4BWAbvA6XPHeeGBz/hl4yfM+v4PrFYrZcqU4fjx44BCg4i2bEuIBYoeKGp1OhKz0nE3WnA3upKTkYRG0aDR6LDbCtm7dy87d+5k3bp1fP311yiKwrRp03juuecwGk8z65cK9O55HJtNw47tCgUFNmx2By9M3EbQr2+xdu1aMjMzEREqV66MiODvZ6JtmwQUBbQaDQaDls2bU/nu21RcLXq83C1kZ2c5Z+8LkGa3MyDqUU54nWLe74vQarWY3ExotVp0ip1mSws4bNdQqFXws7iTnpeFv02D1VVHlp8OnVFHjT41WPveWsI15VkXH0e11yNwsxtY//ZORIRNmzYRHh5OUlISWq2W/Px8HnnkEcxmM0FBQaxfv56QkBDKlClDfHw8ixYtQkTYu3cvs2fP5rPPPmPGjBlUrFiRAwcO0KFDBw4dOoTFYiEiIoIGDRpc83uu+shVVIpT6kfkdqsdFx8XghsF47D4ApAR6c6WLVvIzc3FoNPgbyn6xzdpIdw7B2teAadOJWIrcJCUmAgomPRm/jowHcd5v6sANpsNh8OOzWHjROZpBHDgoNBuxag307pSa4b2H8LI4W8yokovAgr96NSxE/n5+ZStoPD6a6exFgqt27TAr2wg1oICyoZXIKRRZVatXkVufh4mixmjiwmTqwtGi4G0DCsuLgrlyulB0ZJvdTDgyacJ8A8iK9uGp1coYRXD0euMlPONLFq1x6cSP+dqWHzIDXeTD37efugderBCTqqVDfNOEVUnCpPRjI9HWcqWC6GT1UzQ0ULyU/LJOpHFie9P4OfrRwOfFtjy7Rz7NpF9v5xAq9Wi1Wpp3bo1/v7+1KhRA0VROH26aL1UnU5Hp06dnD70p59+mo4dO7Jz506GDx+Ow+GgZ8+e7N+/n2bNmhEVFcWaNWtYtGgRvXv3ZsSIEdcl4v9EVB+5igpwFwh5/YH1Sd6dzMYJG4nzDADg9YHTnIsrW+2g8yyahFLogLdmvUlKRiInzx4ivyCXQpsNEHQaA9sS9jrbVf4RrJddkHfeD6Wg1+rR6/XY7Fa61O6Gm4s3AR7lOUN5okNtiMPG8xGh7NzgILp5bXSNY1i6fgvHCovaS7v/cdY//H/kunqg1G1IvtaIVK1NXn4h1gKwa40UWLV4aGuCo8jt8f0P0yjIKfKF7dqzk+PHTwIKFfxD0Ov15Ek6f26dzsrdc3CInWrVauDl5VUUiSLC4cIC4nbsYOXKlTRs2JCEQwlMTU/DYRcsFgsmk4myZcuSn5/PnDlzKFu2LA67g3O7zgFQu3Ztdu3aRXBwMDVr1sRut1OxYkXGjh1LfHw8c+bMoXv37sydO5dp06axatUqwsLCGDx4MOHh4SxYsIBff/2V+Ph4KlSo4LyvI0eOpHfv3tf/pqsDchWVYpR6Ia/xWA3C7wtn8QuLUQ4/wPdJtTmcDjX8FSz6omiNs6cTgaL//36NA4iOjsZh/0dOcjRkW9PRa3TULO+BApiMBudxrVIUx+1AcDO7YbPZ0Op1dB7bgTxDNs0eakzbwRGkZGWjURTiMtNx8yjH3NPNcFEC0bn4osvJAqDwi4+IWD0VrTUXx97tSEYamoRDUFgAhQU48vKx2e3sTIij0F60MlGBzUpm3lm0Gu35/TwKbPms2buY/IJ8QkJCqFuxOa8PGIveIOzbs5NTJ0+eX4/Ujp9Gi0ajYcCAAXzzzTf4+vqS7xC2WfPJyMggJyeHjTs2kpWTRVpaGm+//TZZp4rsHTBgAL6+vvz111+cOXOGXbt2ATBo0CCgaFTs5ubG2LFjef/99zlw4AB5eXl07doVrVbLhx9+SMeOHYmOjuapp54iICDgln0WVFTuVUq9j1zRKFTtXpWDCw7i4uXCmIUH0Srg5eWNNjsTCguxKTrAhs5oYHGSO81b1WX8hPFF5ysKfr5+JKecQWvQs+tEJgLkWwvQKBoc4sAuf2cKPJd1DkVRsFqttGzZkqCgIGw2G/Eb4og7dgqzwYjD4cBbX8AZg4H0vauwpZ8GcaDTwJePBTN4zASwCT7eHiQrCvmpZwFw9QwkJ+M0Li4uF60vWmi7eHbnBeK2xgGw4cCiooLis/NJsBVCdiE7duxAo9EUC0ME0OoUbNk20EBWVhajR49G46LBke+gfPnyNG7cGLvdzrvvvstPP/3E6tWrmTNnDvXq1aNJkyY0aNCARx55BBFh4MCBxZZ2a9u2LW3btr2et/TaUT0rKirAXTAiz0rMYsXrKwioFYC1opW07Bw0ioZUhz85Oi8AbLaiSS+Tp3xLy7YdKFeuHB999BGKomCxWHjjzaKcISaTkfp16wFFuUx0igZPsxtmk9n5gM3T1ROLxcLy5cvZvXs3CxYsYO3atRzft5uGoeWpFFGZEDcP8gsLCbdY0OenoXVxRauAzQFfLkrAWujA0yCkpaZTo3Fb0GhBUbDnFD34zD8fjXIruNQapeIoujati5bXX3+d9PR0JFfQumnx8ffB29sbo9HIzJkzMZlMdOjQgY8++ogmTZoAMGbMGP766y82btx4y9bn/Cfqw04VleKUaiHPPJXJ1JipWDOtNPm8I2/t/AmNjwcORSFfjjKkf9FI2sXFhdWrV1OtWjWCgoIYMWIEiYmJuLm58f777zNkyBA8PT3JzMxk9949KChoFQ1NKtTFy+xJJa9yeBrdALAWFrB06VJatmwJgJeXF4MGDeKjX6bx46bdfDV5EjqzkZ0nT+OdcYC6desiedk4BPxdICPPgc0BvhYotMPODUtBo+Du7uUc+f8zV/jtwOFwYHYzo/PU8fnKz/F+yBu9vx6xCq3atSIsLIzw8HDmzp3L6NGjWblyZTFfd0mhPuxUUSmi1Aq5NcvK962+J/t0NvXmdOOHTT9zVPkT48Na7HY7gwePYe4fRalcY2Nj0el0LF26lBEjRjB69GgA3nvvPYYMGQJAq1ateOedd4rCABEqlCmHd1l/UvJSOZaeSFp+0cPThpFNadSoUTFb+vXrx7D7ujK8S3dMHoKnxUj7ahEsjP2T7fv306ZNG/QGA0aDjpVPWAA4lK5gGTQc3+nz0CsK/fo+ToEtHwUFH7eblyHwWinMK0STqSF7ezb5G/IpSCygQoUKVAquhFar5eOPP6Zjx44MGjSIgIAADAbD1Ru9VagDchWVYpRKIS/MLeSXh3/h3MFz9JzXkz76XFwyinzKrpVdCa0UygsvvEBCQgJPPfUUP/zwA+3atWPEiBEAfPTRRwQFBTlFHIrE/o033mDbtm2ULVuWgycTeGXcW4gGNIaih4UVAiIZ8vj7l7TJYcsHRUErRY8dGlQsxyduRh5yOKi1fQcFNjtJ2iC+rzoeFAVFb6JtWV+67dmN3WYjeWshCgoGvZmM3HO0ad3ymu6Fch2qdrmaer0eAKPGSF5GHrlJubhaXMlNyWXKlClYrVaaNWvG2rVr+fXXXzEYDHh6el5zv7cMdUCuogKUwoed9kI7vzz8CwlLE+gypQshLULYVVDIqjIWmh6JIqZ1W/RPGC8677PPPnO+zsjIuOj4uXPnLiqLiopy5tn+/vX1ZJ3LJ+lQBku+2QMiiEDRr3vBbtOj1QuLRn0MgEWM1DKZmZBylud8Lbi4B5CfdpL3hj6PWafDy6Bj0TsjiagYgtFgIHb3QrQahSZhIWw8nc5hpRAUBRSNM1nWpbhaXvLidS+NzWajXbt2NGrUiLCwMFq3bk3Xrl2pUaMGAwYM4MSJEzzwwANYLBbsdjuTJk0qUT+16iNXUSlOqRJyEWH+M/M5uPAg9311H3X61QHAz6Cne5VwqBJ+y/oOqeHLsd1nQVFIPpqJoikSkwuaotFpyc865qxf2bcFv3XLoky8jo/+ysKec44XnhqAi8nMp5O+IrRsIG83e4ffNs/nqO4cT7R+nflrXyQzfT+9nwxnwexdRd8ScjV/+aVXaL4QcXMtlCtXjgMHDuDp6cmqVav46aefmDFjBmFhYc7jF5KO3UmoPnIVlSJKlZBv+3Yb27/bTvO3mlP/mRvLnHe9NH80Aoi47PHl351m5/KVuGn1eOl0lHUJ4/3X5jN5wlecrpnKtm3bmLVgIYqi8FCPR1i4cCFzdk+jTdUuJJ9ZQM65zxhQ24arwcCYWSkkF/hg8nHFnpF8xdBDr/KRZJ46VGxtT6PRiFarvWgxZ0VRMBqNF0XFpKen4+3tzbRp0zAaL/41c8dxYUCu6riKClCKhDx5dzJ/DvmTkJgQYt6OKWlzLqL1k11p/WRX8tPzOfvJVrDaOf1JHCEFvpzWp1KnTh1GDB7MX9u2kZ2bS5MmTdgWt52slDgmdSpApznC0sMOnm9o5Gj1AYyPPY7GxYN+trN8s2kp6bmZxfrTaDS0bduWvXv3kqPVYDS6ICIEBgbSokULli1bRn5+Pg6Hw+mKCAwMJDs7m8Lzecx1Oh1ubm54enryzjvvlA4R52/XijoiV1EpolQIuYjwZY0vAej2UzenW+NOxORpouybjUj9+QB5u85SnXKc0aRzRJvMsnXrgCJXRc+ePQkMDCxa2zJ5P+Seo7bOCCn7eceazcC6Ibi1fxKTi5FBmUfIXPketW0OeHhqyV7gnYA6IldRKUapEPJ9c/Y5X1v8LSVoybWh6DR4PxqJvVMoaBTyf9wLZ4pcHvfffz81atQofoJ/5b9fBxe5jP4ZgFjRsyI8+O2tN7yUoI7IVVSKUyqE/MzOoinlT21+6o4ejf8TRatB52UCoP9T/cnNzcXV1RWNplRGfN5ZqCNyFZVilApVqftUXTzKe/BD2x9I2pZU0uZcNzqdDnd3d1XEbxLqiFxFpTilQlk8ynnwROwT5Kfns/nzzSVtjkpJo47IVVSKUSqEHMAzxBNFo6B30Ze0KSolzQUBLx1eNhWVW06pEXIoEvOdP+xk85ebsRfe3sRSKncOF1wqpeV5iYrKrabUCLmiKDzy+yME1Axg4aCFfFn9S/b9tk/1k96DiOO8kKtT9VVUgOsQckVRtIqibFMUZf75fW9FUZYqinLw/F+vW2dmEQE1Angi9gkenfsoilZh1kOz+KLaFxyYe+BWd61yJ6G6VlRUinE9I/KhwL5/7L8CLBeRcGD5+f1bjqIoRHaOZODOgXT5tgsarYaZD8zkyxpfsmTEEs7uP3s7zFApQVTXiopKca5JyBVFCQbuA6b8o/gBYNr519OArjfVsqug0Wmo82Qdno57mg6fdcASYGHD/zbwR78/bqcZKiXB+RG56lpRUSniWkfknwL/B/wznV6AiCQBnP/rf6kTFUV5WlGULYqibElJSbkRWy+J1qCl4fMN6bOsD01fa8rJDSeZ03MOJ9afuOl9qdwZXPCRq64VFZUirirkiqLcDySLSNx/6UBEvhaR+iJS38/P7780cc3EjIwh+pVoDi48yLfR3zKr2ywKsgtuaZ8qtx+na0UdkauoANc2Io8GuiiKchSYCbRSFGU6cEZRlECA83+Tb5mV14hWr6XNmDa8mPgiLd9ryf7f9zOl0RRObT5V0qap3EwuDMhVH7mKCnANQi4ir4pIsIiEAI8CK0SkNzAXeOJ8tSeAO8Y5bbAYaP56c3rO70l+ej7T201n14+71FDFuwTVtaKiUpwbiSP/AGirKMpBoO35/TuK8I7hPLn6SXwiffi116/Mf2Z+SZukchNQXSsqKsW5LiEXkVgRuf/863Mi0lpEws//Tb01Jt4YXhW96LeuH1UeqqKOyu8WVNeKikoxSs3MzhtBo9UQ1jGMwpxC1oxeo4p5Kcf5/qk6rqIC3CNCDlCzd03COoSx8s2VnFinhiaWZtQp+ioqxblnhFxn0tHhsw4AJO8p8QAblRtBda2oqBTjnhFyANP5FXsSliSUsCUqN4LqWlFRKc49JeSLhi4CBSo/WPnqlVXuXNQp+ioqxbhnhNxmtbH/9/3Uf7Y+NXvXLGlzVG4ANY5cRaU494yQn9xwEluejbAOYSVtisoNomY/VFEpzj0j5GcPFKW39a9xydxeKqUJ1bWiolKMe0bIy9QqA8CBP9RFKEo7qmtFRaU494yQBzcKpkLzCqwfu17NiFjKUV0rKirFuWeEHKDV6FZkJWaxccLGkjZF5UZQXSsqKsW4p4S8fNPyhLYOZfW7qzmz60xJm6PyH1HjyFVUinNPCTnAQ9Mfwuhu5Lfev2Gz2kraHJX/gHOKvupaUVEB7kEhdy3jSufJnTmz8wyrRq0qaXNU/guqa0VFpRj3nJADeIV6AbD9u+1qJsRSyIX37Oiqo+qDaxUV7lEhn/f0PExeJh757RF1VFcK8QzxJKxjGHFfxfFpyKesGbMGa6a1pM1SUSkx7kkhN3uZ0eg0+FdXJweVRvRmPb0W9qL/hv4ENwxmxWsr+DTkU1a9s4r89PySNk9F5bZzTwp5szeakZuSy7fR33J83fGSNkflPxLcKJjHFjzGU5ufokLzCsS+HcunFT5l5VsryUvNK2nzVFRuG8rt9BHXr19ftmzZctv6uxL7ftvHoqGLyDyZSZsP2tBoWCO0em1Jm6VyA5zefprV761m35x9GFwNNBjSgMYvNsbF16WkTVNRuSEURYkTkfqXPX6vCjmANdPKr71+JX5+PP41/Gn3v3ZUbFNRDWsr5ZzZdYY1o9ewZ9Ye9C566g+sT5OXmuAa4FrSpqmo/CeuJuT3pGvlAkZ3I4/OfZRHfnuE/PR8prefztf1v+bgnwf/zudxjzFgwABMJhNarZaIiAi2bt3qPPbAAw9gNpvR6XQoioLRaGT48OF8/fXXmM1mtFot3t7e9OrVi+TkZBo2bIinpyd6vR5FUXj00UdvyzUE1Aig+8zuDNoziMpdK/PXuL/4LPQzFg1bRFZi1m2xQUXldnJPCzkUxSJX7lqZwQcG88B3D5CTnMOPnX5kYuRE4ufHl7R5t5UjR44wY8YMKleuzJIlS0hMTOT55593Hv/jjz/Iy8vDZrPh5+dHREQEDz/8MMOGDSMkJISEhAR0Oh3JycnExcXh4+NDvXr1+OOPP2jfvj0zZ868rdfjV8WPh6Y/xHP7n6P6I9XZNGETn1X8jIWDF5JxIuO22qKiciu554X8Anqzntp9azM0YSgP/fgQOpOOmQ/MZNU7q+6ZWPMZM2YQGBhIixYtaN26NXa7nczMTKzW4qF9+/btIz09HZvNRqNGjSgsLKRBgwakp6dTuXJl9u/fj81mIzU1lV27dtG9e3d2797NnDlzSuS6fMJ9eOC7BxgSP4Saj9ckblIc4yuNZ/6z80k/ml4iNqmo3ExUIf8XWoOWGj1r0H9Df6r3rE7s27HM7DKT3LO5JW3aLScpKQmj0YiXV9GEKaPRiF6vJzU1tVi9N954g/Lly9OjRw9nvfLly9O+fXvWrl1LYWEhvr6+7Nq1i/z8fLy9vbFYLLzxxhukpaXd9uu6gFdFL7pM7sKQQ0OoO6Au27/bzoTwCcwdMJfUw6lXb0BF5Q5FFfLLYHA18OAPD9JhfAcOLznMV7W/4vSO0yVt1i3D4RACAwMpKCggPT0dAKvVSmFhId7e3sXqLl68GJ1OR+/evQGYPn0677//PlarlZCQELy8vNi0aRORkZGUK1eOFi1aEBUVRUhICAcPHrzdl3YRnhU8ue+L+3j+8PPUH1ifndN3MjFyIr8/8Tvn4s+VtHkqKteNKuRXQFEUGg5pSP+/+gPwdb2vmRozlaOxR+8qd8vMt6dx/JUVtDwZTlJSEqtXr2bNmjVotVrc3d0xGo3OuosXL8bhcODp6Ul4eDhQ9BA0LCyMffv2kZ2dTUxMDAaDAREhMTGRBx54gD179nDq1CkqVKhQUpd5Ee7B7nQc35GhR4bS8PmG7PllD59X+Zxfe/1Kyt6UkjZPReWaUYX8GgisE8hTm56i6StNObvvLNNaTmNc0Dj+6P/HXTHxxOxSiE5joIJnED26P8zevXuJiYkhMDCQTp060axZM8aOHQvA6NGjqVChAr169XKe/8ADD3Dy5EmCg4Mxm82cOnWKxx9/nFGjRpGTk0P//v1JT09n4MCBBAQElNRlXha3QDfaj2vP0CNDaTy8Mfv/2M8X1b9g9iOz1XTHKqWCezqO/L9QmFvInl/2kLA0gb2/7MW1jCtdv+9KSIuQkjbthnAU2FG0CopW/W7PPZvLhk82sGnCJgqyCqjSrQoxI2PUlA4qJYYaR36T0bvoqf1EbR6a/hBPrHwCjV7DjI4zyD13ax6GTp06lSZNmhAdHV0sphvgo48+omHDhkRHRzNkyJCL3D0tWrRgwIAB19SPxqBVRfw8Lr4utB7dmheOvkDzN5tzeMlhvqz5JbMfnU3KPtXlonLnof7n3gDlmpSj4/iO2PJszHpoFr8/8Tvznp7Hn0P/JP1Y+g23n5aWxttvv42IYLVa6devX7HjFSpUIDc3l7i4OI4cOcKKFSsA6NOnDzVq1GD37t388MMPzJs3j9TUVGJiYpybXq+/5giSK32ZjBs3ztlmaGgow4cPB2DDhg00adKE5s2bO90yAJMmTaJhw4Y0a9aM5cuX38jtueWYvc20fKclLxx9gaavNiV+fjxfVPuCOY/NUQVd5c5CRG7bVq9ePbnbsNvsMvvR2TI+fLx8UuETGeM+RkYyUn5/8vcbbnvWrFni5+cnVqtVEhISxMXFRfLz853H09PTJSsrS1q0aCEPPvigxMbGFtlkt0uHDh1k7ty54urqKnl5eSIiEhERIRQtyyCKosj06dOdbQUEBDiPXdjq1asn7du3L1ZmMplk27ZtoihKsfJq1aqJ2WyWnj17iohI5cqVpW7dutKsWTOpXLmyHDhwQM6cOSN16tSRgoICyczMlHr16onNZrvh+3S7yEnJkaWvLJXRltEyUhkps3vOluS9ySVtlso9ALBFrqCtqpDfZArzC+VDnw/l46CPpSC34Iba6tixo7i6ukqTJk0kLi5OLBaLHDlyREREfvrpJ4mOjpZmzZqJm5ubNGjQQBwOh6xfv14qVaok4eHh0rZtW4mIiBARkVWrVjlFNzw8XABxc3O7ZL+KoojRaJTJkyc7z4mNjXWK98cffyzBwcFSvXp1ee2110Sv10vNmjXFYrHIhg0bRETEaDTKsWPHREQkLCxM3nnnHdm4caP06tXL2U/z5s3lwIEDN3SPSoKLBP1RVdBVbi1XE3LVtXKT0Rl1PPj9g2QlZrHi9RX/qY2c9DRSzpwhLi4OPz8/8vPziYmJwW63O+s89NBDrF27lokTJ5KTk0N8fDyKojB48GDy8vIoU6YMK1asIDe3yHf/zjvvoCgKbm5uzjjxgoICMjMzi/U9f/5854fjgn9dURTc3d3R6XQAHD58GIfDQXJyMpMmTcJoNJKZmYnBYKBRo0bOc9LS0igoKCA/P59t27YRFhbG9u3byczM5NSpU+zYseOiyUalARdfF9qMacMLR18g+uVoDsw7wJfVv+T3J34nLaHkJjyp3LvorlZBURQTsBownq8/W0TeVhSlNvAVYAJswCAR2XQLbS01XFitxreK7zWfIw4HP7z6AilHEwDYn5SMQSnKf+Lt6YmHhweJiYkEBgYCYDAYOHToEG3btkVEnLHeKSkp5Ofns3v3bux2O0lJSYwaNYpdu3YhIuTl5VGuXDlSUlLQaDQkJCRQu3Ztpx3PPPMMOp3OKcharRa73U7dunWddVxdXYmNjaVr164cPHgQrVbLsWPH6Natm7NOZGQkAwcOxGKxYLVa0el0eHt7M2rUKDp37kxAQAC1atUiKCjov93kO4ALgt5keBPWfriWzRM3s+vHXdTuV5sWb7bAPdi9pE1UuVe40nC9aESPArief60HNgKNgCVAx/PlnYDYq7V1L7hWMk5kyNiAsTKp3iSx2+zXfF5eVpb8r8d9Mn1slCxeGCZDBgaIxaKI2ayIVvu3P/qhhx6Sjz76SESK/ND8y68NyBdffCFRUVHOfW9vb9HpdBf5tQHJyMgoZgcger1eFi9eLEeOHHHW02q1ztfPPvusiIjUrFlTzGaz6PV60Wg0Th+9iMju3bulffv20qZNGwkKCpIJEyYU6ycxMVE6dOjwX2/zHUlmYqYsGLxA3tG/I+8a35U/h/4pWaezStoslbsAbtS1cr6d7PO7+vPbhX/qC0MODyDxv32V3F38eP+P5JzJoeHzDfmi2heMUkYxMXIiq99bTU5yzmXP2/DbarKq1KNM3XNojQ4mf3eGnBwhL0+w24vCCgMDA/n111954403UBSF/fv3O8/Xav9eFGPQoEFs3rwZgJplfUlNTcVmsznDEw0GA/C3y+QCo0ePdh7vo/en0ZF0NBoFnU5HrVq1nOfodDqaNWuG3W7nhRdeQEQwGAy0aNHC2dbixYuxWq0UFBQQFBTEI488AhRF1LRs2ZIBAwYwYcKE/36j70DcAt3oNKETQw4OoWbvmmyauInxFcez7JVltyw8VUUFrjH8UFEUraIo24FkYKmIbAReAMYqinIC+B/w6mXOfVpRlC2KomxJSbn7Q7YuLOb8+xO/c+5AUd4Oj/IerHxzJRMrT7xkrnMRwb4/Ewcavjd9yf/+bEZ+PhgNCq6uRYshuLu7O9uuWbMmP//8M6GhoQDo9Xqn/xrgiy++AMBisXAk+WIfdEFBgbNfg8HAfffdBxTFpev1ejp06EBr16Lvbj9/L2w2mzPsMCIigvLly7N27Vr27NnDmDFjsNlslClThoCAABRFQVEURowYwZkzZ9BoNIwaNYqKFSuiKAo//PADsbGxLFy4kEcffZTQ0FDnOYqiULZsWbZt24ZGoylW/sADD9yEd+f24FnBky5TuvDcvueo/GBl1n20jvEVxxM7KlZdJFrl1nCl4fq/N8ATWAlUB8YD3c6X9wCWXe38e8G1UpBTIEdij8juWbvlwLwDYi8scq+c2XVGPg39VEYyUr6q/ZUcXnZYdv20SxLjEkVExJaeL5vjk6XHK2OldoBGNCAtKmic7pDAwEAxmUwCSEhIiGg0GtHpdBe5Pf65mc3mYiGHFzZXV1cxmUxiMpnEx8dHmjZtKsuWLbuh654/f/5F/Wg0GufxS7l1Lrd17dr1ojKDwXBD9pUkZ3afkZ+7/SwjGSkfen8oaz5YI9Zsa0mbpVKK4Cquleueoq8oyttADvAm4CkiohQNFTNE5IpPd+6GKfo3gi3fxs4ZO/lzyJ/Y8mzFjvVe0puPk9NZvOsUBV8+QHI21AjQkOMRwf79+9HpdHTu3JnffvuNoKAgkpKSnK4Sk8lEfn7R6vGKolw0w/PfaLVazGYzNpuN5s2bs2nTJtzd3cnIyGDixInOrIbXwwWb/k1GRgbu7u64ubmRnZ1d7JhGo8HhcFx0zttvv82oUaMuKt+yZQv16tW7btvuFBLjEol9K5aDCw9iCbDQ7LVm1Hu6HjrTVWMOVO5xrjZF/1pG4X4UCTaAGVgD3A/sA2LOl7cG4q7W1r0wIr8Wcs/lSvyCeDm56aSMZKSMZKRMazVNRES+WXNYvPzKiEZBXmtVSapWrSqAPPPMM1KlShUB5PTp0+Li4iKA+Pn5OUetvXr1umgkGxYW5hzRXii7MJIHpEKFCtKuXTvRarXi4eEhlStXFp1OJ6mpqdd1Tf/sc8SIEc7XEREREhcX56yn1+udx8qVK3fJEbmbm9sly+vUqSPvvffeTX0vSoLj647L1JZTZSQjZVzwONkyaYvYCkrPxCiV2w83OiEIqAlsA3YCu4G3zpc3BeKAHRRFstS7WluqkF/Mtu+2yUhGypoxa+S7xUulwsvzJeixNwSQxBfM8u5rLxUTMz8/P+nSpYtz/8CBA8L5mZphYWGi0WhEo9FcJIKXc20YDAYJCQkRrVYr/fv3l9q1a4vBYJD+/ftf13X8s83U1NRiXy7R0dGXrPfv/QvbP8X+n9v48eNv6r0vaRKWJ8iURlNkJCPls4qfyfbvt19XpJPKvcPVhPxaolZ2ikgdEakpItVF5J3z5WtFpJ6I1BKRhiISd7W2VC6mdt/aeId7s33qdpTYFLyTc6nYsiY+rl4EfZrHm+//jw7VWtCpRgwAFcqVp3Xr1s7z8/LycHV1pXLlythsNhwOBw6HAy8vL/R6vfOBqPzD3XLmzBmio6NxcXFx5lwpX748bm5uuLm58dJLL12z/XsTt7H1XxOf/rnOZ3R0NNnZ2VitVoYNG+YsN5lMnDhx4pJtFhYWXrL83XffZfv27dds251OaKtQ+q3vx2MLHsPoYeT3Pr/zZfUv2fPLnnt28W+V/4aaxvYOYOVbK1n97moAXANdGZ44nJOvrLmo3muLP+bHHfOpVCkUi5sb27dvR6vVYrPZCAkJITg4mPXr12OxWHBzcyMpKQmDwYDVakWr1aLRaNBoNOj1eqe/WqPRFIt4KSgoYNCgQVitVqZMmXJV24O/Xo0uIYucz3txNvviBY0NBgOurq7s3r272OSf7777jvj4eMaMGXPN96l///5s2LCBPXv2XPM5pQVxCPt+20fsW7Gk7E0hoFYALd9tScT9Ec5oJZV7FzWNbSmg5TsteenMS1j8LdgL7IgIpufKs+bMHHamrmK31yT2hr/Lg60D8XJxIT0rmR27diAiPPfcc1gsFo4fP86HH37oDFNUFAVfX19mzZqFRqPBbrdTWFiI1WqlZcuWREZGAkVCXlBQ4NygKHxRRPj6669xc3PDw8PDGaII0K9fPwICAopWAVpStKByz66hl7y2goICUlNTL1ourm/fvpfNfuji4nLJ8scffxyLxVKi637eKhSNQtVuVXl257M8OP1BCrILmNllJt80/oaEZQlXfYCtco9zJb/Lzd5UH/nlSdqWJCMZKRs+3eAsy0g5Iyf375Rlyys6t1fLB0sts1lcz/vBK1SoIFWrVhVFUaR58+bi4uIitWvXloCAAPHw8JC6des6/c5BQUFOf3Pr1q3F09NT7r//fqlRo0axh6GAGI1GcXFxke7duzt97t7e3lJYWChr16792/d+/u87D3YRP6/iDymrVq0qOp1OzGaziIgYDAZRFEVq1aolBw4ckIYNG4qrq+tFvnAXFxexWCzFHs5WrVpV3NzcRKPRiFarlQufpUmTJomrq6u4u7tLp06dnPeuXbt2zna6dOlye9/Mm4CtwCZxk+NkXLlxMpKR8l2L7+TYmmMlbZZKCYGaNKt0cMEnanA1OMvcff0pG1mDGjWKJvh4fqvlcbMr34VHUKVePby9vdGdz3Pi4uLCww8/jL+/P9u2baN///5ERkZy5MgRLBYLFSpUIDEx0TkDdPny5eTm5mK1WjGbzQQHBzsn9AAEBwdTWFjIr7/+yi+//ELz5s1JT0/ngw8+oFy5cpjNZurUqcP9PTphdDfSY8pHJP/+JvK2OzJvGN988w0eHh40aNCA1atXs337dt577z0cDgfbt29n+vTp9OrVi6ysLESEhIQE54zRiIgIHA4HIsLx48epUaMG3t7eVK9enWXLluHt7c2zzz4LwLBhw1iyZAkZGRls3ryZxYsXk5iYyMqVK0lLS+Ps2bP8+eefJCcn386384bR6rXUHVCXIQeH0HFCR84dOMd3zb5jeofpJG5RJ1Gr/IsrqfzN3tQR+eUpzC+UCRET5F3DuzK5wWTJOZtzUZ3jg56TPZGVZdaDD0mLli2lTJky8vbbb0uvXr1EURRp0KCBbN68WbZt2+bMx6LX68XT01N0Op0YjUaZPXt2sZGur6+vfPbZZzJ79mwxGo3O0XdAQIBotVpRFEXWr18vrq6uotPppEOHDtKvXz/x8/NzTizq3r37DV//u+++K7Vq1XLum0ymi/LAiIjs3bu32OQgvV7vfN28eXPp1auX5OXliYeHhyQlJcmpU6fEZDJJVlbpznlSkFMgaz9aKx/6fCgjGSkzu86U0ztPl7RZKrcJ1BF56UBn1NFnRR+qPVKNU5tOseHjDRfVKff5RHqN/4khQ95k94DhnDt3joKCAjp16oSrqysbN26kfv361K5dmxEjRrB48WIMBgPDhw/HZDJRpkwZunXrhslkQqvV4uLiwurVq3n++ef566+/cDgcBAcHYzKZOH36NHPmzEFEaNKkCXl5edjtdjIzM1EUhcmTJ1OpUiUKCgrYuXPnDV9/UlISnp6ezn2j0UhCQsJF9d544w1nZsYL9WbNmkV2djbbtm3j7NmzmEwmGjduTNmyZSlXrhydO3d2pjoorehd9ESPiGZowlBi3onhyIojfFXrK+b0nMO5+HMlbZ5KSXMllb/ZmzoivzZ+ffxXGaUZJcfXHb/o2ODfd0nAim3SePlO6du3r7i6uoqbm5tMmzZNZs6cWcxPHFKurFSpUkVef3K4aLVa8fX1laZNmzpH5C+99JKIiGzevLmYj7p69erONsqUKSOenp6iKIpYLBapUqWKNG3aVKKiosRgMIher5eqVate9wSiCzgKC0WkaEReu3ZtZ/nlRuQWi0WWLFni3P/999/Fx8dHfHx8JDQ0VJ566ilZtGiRWCwWycjIkHPnzonFYpHNmzf/J/vuVHLP5cqyV5fJaJfRMkozSn5/8ndJO5JW0map3CJQVwgqfeRn5MsY9zHyW5/fbqidV0cNkEYffSsVXp4vXo0aOx8kPv/886LRaIqJfrNmzaRu3brF8qN06dJFNBqNeHh4yKuvviouLi7y9ttvy8svvyy1a9cWRVHE29tbwsLCxOFwXLd9BdZCmfjMcvnusfHOpexycnJk/fr1l1y96IJAX4qsrCzx8/OTvXv3ysKFC8XLy8t5zN3dXRYuXHjd9pUGss9ky6Jhi+Rd47vyjv4dmT9wvmScvPgLUKV0owp5KaQgp0BGaUbJyrdX3lg7NrtUeHm+VHh5voxYu1aio6OdMz9HjhwpH3zwgVSuXNlZv1y5csX81CIi9evXF61WK1qtViIiIiQrK0uOHz8u1apVE0AaNmwoK1as+E/2FeZb5fOnFsu0Hm+KiFz1F0azZs2kW7duxdro0qWLeHp6iqenp4wcOdJZ3qhRI7FYLGKxWKRhw4b/yb7SRMbJDJn37Dx5R/eOvGd6Txa9uEiyz2SXtFkqN4mrCbk6IegO5NSmU0xpOIUu33ahzpN1bqgtEbmjJ5Tc6faVNtKOpLH6ndXs+H4HOrOOhkMb0uSlJpi9zCVtmsoNcLUJQaqQ34FYs6yMrzQej3IedJvZDZ9wn5I2qVQxdepUvv76a1JSUjCbzeTl5WE2m3Fzc6Nhw4Zs3bqVkydPcurUKYxGI1arFYvFQlZWFgaDAbPZ7JwBq9VqsVqtpKWlERkZiZeXF9HR0XzxxRdMmDDhP2WKvB2cPXCWVSNXsXvmboweRpq81ISGQxtidDOWtGkq/wFVyEspu37axa+P/YrB1cDjyx4nuGFwSZtUKkhLS6N169ZUrlyZn376qdgxo9GIVqulfv36rF279pIpdP/N5dICX0gD/O23396xYg5wZucZVr61kgN/HMDsY6bpK02JGhSF3kVf0qapXAfqFP1SSo2eNXhqy1PYrDa+afQNa96/OPeKysVs3LiR7Ozsi0QcwGq1kpuby+rVq69JxIFLijgUJSsrLCzk5MmTN2TvrSagZgCP/v4oAzYOIKh+EEtHLGV82Hg2fb4Jm9V29QZUSgWqkN/BBNUL4rEFjwGw4eMNZJ/JvsoZKs899xwHDx68bf2VKVPmtvV1I5RtUJbei3rTd1VfvMO8+XPwn0yMmMjWb7bisF3bl5rKnYsq5Hc4ldpWouPEjuSl5fFds+84vvb4ZUeJ9zK2Qjsb12++5CSiW8W/10otDVRoXoG+q/rSe0lvXMu4Mm/APL6o9gV7Z+9VP1elGFXISwENnmtA78W9yU/L57tm3/FFtS+IHRlL8u7kG/rnmzp1Kk2aNCE6Otq5uPIFxo0bR0xMDDExMYSGhjJ8+HAANmzYQJMmTWjevDljx4511g8NDXXWHz169H+26XrJzSxg+ff7mDRkFb27P31N53h5ed2UvgsLC9mw4eIZuHc6iqJQqW0l+v/Vn0d+fwSNXsMvD//ClAZTSFh++74IVW4iV4pNvNmbGkd+YxTkFMjmrzbLdy2+k5HKSOdivgcXHbzutlJTU6VOnTpitVolISGh2Co+/6Zjx46yYUNRVsb69evLsWNFWfg6deokBw4cEBGRSpUq/YcrunFW/XRAJj6zXCY+s1yMOtMlVxa6VZuiKFK+fHnZuHFjiVz7zcJus8u2qdvkk/KfyEhGyvdtvpdTW06VtFkq/wA118rdg95FT/1n6tM3ti8vnnyRzlM6Y/QwsvLNldfd1nvvvUdSUhItW7YkLS3NuYoPFB+Nly9fno0bN9KoUSM2bNjA7t276d27N2PHjqV+/frExsYCYLfb0ev11KxZ87au4uNX3g2NpigO3XGbXQMiQo8ePWjQoMFt7fdmo9FqqP1EbQYfGEz7T9qTtC2JyfUn80uPX9Q8LqUEVchLKW5BbtTtX5fGLzYmcXMiiXHXnto0LS2NOXPmMGDAAKZPn87zzz+Ph4cHqampALz44ovExsYSGxuLq6srXbt2BYqWcKtatSoTJkxgxYoVzJs3z3lOp06daN++PY888gi9evW66dd7Oao0CcT3MQ27XTPw9bl6jLTRePPiqF1dXZ3RL3/++SdRUVE0a9aMXr16YbOVvogQnUlHoxcaMTRhKM3fas7BhQf5vOrnzHtmHpmnMkvaPJUroAp5Kafm4zXRu+jZ8tW1x+dv3LiRWrVqkZWVRWhoKNnZ2aSnp1+0ik9KSgpHjhzhlVdeASAjI4Pvv/+el19+mfj4eAwGA0FBQRw/fpyMjAzq169PhQoVbvsqPqtXLGSPJY0aza/sI+/UqVOxh5MajQaLxXJdfZUvXx6DwcAbb7yB3W7n66+/xmQycf/991O7dm1ee+015s+fj7u7O/7+/nz44YcANG3aFE9PT9zc3IiMjOROnk9hdDfSclRLhiYMJWpQFNu/286EsAkse2UZeWl5JW2eyiVQhbyUY/IwUf2x6uz+cTf5GflXrZ+cnEx8fDyRkZGsXbuWwsJCjEajc/snn332GT4+PoSHhwPg6+uLzWZj7ty5+Pv7k56eTseOHXnrrbecCzanpqaSnp5eLCXtrSaCDFprjvJ4wyO4mwyXrGMymUhMTCQ3NxcoWkvUy8uLDh068M4771xU32y+9JT2pKQkevXqxebNm51roRYUFKDRaGjevDm9evUiM7No9KrRaJgzZw6bNm1iy5YtRb5MjYb4+HiGDBlyk67+1mHxt9BxfEcGHxhM1e5VWffROsZXGs/6j9djyy99vzjuZtSZnXcBe2fv5ZeHf6Hz5M7UHVD3svVEhFGjRnHo0CF8fHyoVasWU6ZMYceOHSxduhQXFxeWLl3KiBEjAChbtiz9+vXj3XffBWDPnj1069aN5ORkDAYDvXr1om/fvowePZr4+HjOnTuHwWDg66+/pmXLlrfl2i/w45TppG1YTrLOhb5RNSj3QDd0fn7X3c4zzzzD9OnTnYIP4O3tTVpaGmXKlCE/P/+yvzb+OQtUo9HgcDjQ6XQXuVlcXV2pX78+K1de/7ONkuT0jtMsf2U5hxYdwqO8By3fa0nNXjVRNGqunFuNOkX/LseWb2Ni5ESsWVaeXP0k/tX9L1v35Ctr2KM9wWFrIt/GzmTDhg0kJSXx2GOPsXbt2mJ14+Pj6dOnD3/99ddF7RQUFPDggw8ydepUFixYwDfffIPFYuHQoUNYLBYmT55cah4AZp7L40xCJku+2UNuQRb/913XW96nVqtlwYIFtG/f/pb3dStIWJ7Asv9bRtLWJAJqBdD2o7ZUaleppM26q7makJeu2QwqF5F9JpuM4xlEDY66oohLoR2AavZyRD8Ug6mqNy1atEBRFD777DO2b99ebDR+YU3NfzJu3DjmzZsHwIgRI/Dz86Nv37707dsXgJEjRxIWFlZqRBzg17FbyUkvitaZveaLK9bV6/UUFhbecJ92ux1fX98bbqekqNi6Ik9tfordP+9mxesrmN5+OhXbVKTNh20IrBtY0ubdk6gj8ruAH9r+wPF1x3k161U02ss/9pBCB4VnctCXdVVTx55n9c/x7FpZlC/l+a/b4RD7ZevWrl2bbdu2ERISwrFjx26o3/nz53PffffdUBt3AjarjS1fbWH1u6vJO5dHjcdq0PK9lniF3pxJVypFqEmz7gHqD6yPLc/Grh93XbGeotdgCHZTRfwfNH8kgue+asXkqBevKOIATzzxBMOGDbthEVcUhc8///yG2rhT0Bl1NBraiOcPP0/T15qy77d9TIycyKJhi8g9m3v1BlRuCqqQ3wVU7lqZwHqBLHt5GdYsa0mbU+rYuXwxmSfHXLGOXq/H19eXbdu2FSt3cXG5rr7c3NyoUqUKCxcuvG4772RMHiZaj27NkINDqPVELTaN38T4SuNZM2YNhbk37o5SuTKqkN8FKBqFjuM7kp2UzZ6f95S0OaWOpw69yitnE3HxLnfZOoqi8Oabb140a/WFF164rr6ysrKYOHHif7CydOBe1p0uk7swcNdAKrSowIrXVjAhYkJRlkW7mmXxVqEK+V1CcKNgjO5GkrYmlbQppY4Ic2XqW+bwYqsnL1tHoyn6V8nIyHCWubi4sG7dukvWDw0NvWR51apVb3toZkngV9WPnnN70nd1X9yD3Zk3YB5f1fyK+PnxapbFW4Aq5HcJikahbIOy7J65m32/7VP/Wa6Dxgl1mFehEp71sqjp6wkUPUMIDg7mueeeIyQkhHfeeYcjR45Qrlw5/P39GT9+PDk5OcTGxjJr1iw0Gg1ms5kWLVqQlZXFqlWr8PcviiJSFAUXFxeGDRvGnj331i+mCs0q0H9Dfx6e/TD2Qjs/df6JaTHTOLnxzl6Qo7ShRq3cRZw9cJafu/7M2f1nqdWnFm0+bINrGdeSNqt0YLeBLQ8xuCJiR6NRI3NvNvZCO1unbGXVyFXkJOdQtXtVWr3fSl2T9hpQJwTdYzhsDla9s4o1769BURQqtq1IxbYVqfZwNdyD3UvaPBUVrFlWNozbwPqx67Fb7dR9ui4t3mqBa4A66LgcNyzkiqKYgNWAkaIJRLNF5O3zx4YAgwEbsEBE/u9KbalCfvs4d/AccZPiiJ8Xz7n4cxjcDNw/6X5q9KxR0qapqABFk9lWvbOKuElx6M16moxoQuMXG2NwvXS+nHuZmyHkCmARkWxFUfTAWmAoYAZeB+4TEauiKP4iknyltlQhLxnOxZ/jj35/cGLdCWr3q839X96P1qAtabNUVICiz+fy15azb84+LAEWYkbGUKd/HbR69TN6gRueEHR+gYoLq/7qz28CDAQ+EBHr+XpXFHGVksMnwoe+sX2JfiWa7d9uZ+P4jSVtkoqKE58IH3rM7kH/Df3xifBhwcAFfFn9S/b/vl99aH+NXFPUiqIoWkVRtgPJwFIR2QhEAM0URdmoKMoqRVGiLnPu04qibFEUZUtKSspNM1zl+tDoNLQZ04awjmHEjoxl14+71IkaKncUwY2C6buqL4/OfRRFq/Dzgz8zreW061o05V7luh52KoriCfwGDAFmAisocrNEAT8DFeUKDaqulZInKzGLnzr/RNLWJLQGLe0/aU/UoEt+B6uolBgOm4OtU7ay8q2V5KbkUrN3TVq93wqPch4lbVqJcNOjVhRFeRvIAdpQ5FqJPV9+GGgkIpcddqtCfmfgsDk4svII68eu58iKIzyx4gkqNK9Q0mapqFyENdPKmjFr+OuTv1AUhUYvNqLpK00xut28JftKAzfsI1cUxe/8SBxFUcwUCfh+4Heg1fnyCMAAnL1xk1VuNRqdhkptK9Fjdg+8K3nz430/svaDteSlqst4qdxZGN2NtBnThsEHBlPloSqsfX8tE8ImsGXSFhw2dcr/Ba4laqUmMA3QUiT8s0TkHUVRDMC3QG2gAHhJRFZcqS11RH7nkXkqkz+e/IOEpQm4lnGl/SftqfZINTVDosodyalNp1gyfAnH1x7Hr5ofbce2JaxD2F3/eVUnBKlcE0lbk/i97+8k70rm/q/vp95T9UraJBWVSyIi7P9tP8teXkbqoVQqtq1Iu/+1I6BmQEmbdstQ85GrXBOBdQN5ZtszBNUPYtXIVWou6aswdepUmjRpQnR0NFu3bi12bNy4ccTExBATE0NoaCjDhw8HoE+fPs5yLy8v52pLKteHoihUeagKg/YMov0n7UncksikOpOYO2AuWUlZJW1eiaCOyFWKcXzdcabFTMOvqh+9F/e+p3O1TJ06lSefvHxGxFtJamoqXl7qKjvXQl5qHqvfW82miZvQGrRE/180jYc3xmC5e2aIqq4Vlesmfn48s7rNwmF3ENwomDJ1yhDWPoywjmFXXErubuLzzz/n+eefx+EomQdqiYmJBAaq619eD6mHUln2yjL2zdmHW5AbrUa3olafWiia0u8/V4Vc5T9xdv9Zdvywg2OrjnF6+2kKcwqp9kg1Hvzhwbt+6nRaWhp169bl6NGjJWbD1q1bqVOnTon1X5o5vvY4S4Yv4dSmU5SpXYZ2H7cjtNWl88OXFlQfucp/wreyL61Ht6bf2n6MSBlBy3dbsufnPXzf+nvO7r+7o0w3btyIt7d3idqQkJBQov2XZso3LU//Df156MeHyEvL4/vW3/NT55/u6s+tKuQqV0Vv1tP8jeZ0/b4rZ3ae4cuaX7LyrZXY8m0lbdotITU1FYOuZHN8LFu2rET7L+0oGoUaPWsweP9gWn/QmmOrj/FF9S9Y8NwCclJyStq8m46aPV/lmqn1eC3C2oexZPgSVr+7mm3fbiO4YTB+1f2o0bMGvpV9S9rEGyJn61ZO/P4r2+U3HBwpUVuud1FnlUujM+lo+nJT6vSrQ+zIWOImxbFr+i6avdGMRkMb3TVZQFUfucp/ImFZAlu+3ELK3hTO7j+Li68Lw08PL9UPQxe3bM5hDzPl28Xz4kenOJWkJbcgv0Rs2b17N9WqVSuRvu9mUvalsPSlpRxceBDvcG/aj2tP+H3hd/yEItVHrnJLqNimIj3m9ODZHc/iUd4DnVl3x/8zXImCfBu7/d3JM+o5G1eOJ/yq423yvO12+Pn5ISKqiN8i/Kr48diCx3hs4WMoGoWfOv/EjI4zSNlXujOzqkKuckPsnb2XjOMZtP+kfakO89JqNehdOgAwT9+WRc3fYOXTMxgYMxCT/vquS6PRXPeXmouLCyJCcrKa1v92EN4xnIG7BtL+k/ac/OskX9b4kkUvLCIvrXTmG1JdKyo3RPz8eH7q/BMNhzak7di2d01o4pFcK1uSM+lczhuT9u64JpVLk5OSw8o3VxL3dRwuPi60fK8ldQfUvaPchGocucotRURYOHghW77Ygm8VX2JGxVDlwSpodHfOP4GKyrVwevtpFr2wiGOrjhFQM4AOn3UgJCakpM0CVCFXuU3s/2M/y19dztl9ZzF7m4m4PwK/an4Y3Y0E1Q8iqH5QSZuoonJVRIR9c/ax5KUlZBzLoGr3qrQd2xbPEM8StUsVcpXbhsPuIH5ePHtn7+XQokPknSvyN2oNWl7Lfe2O+qmqonIlCvMK2fDxBtaOWYs4hMYvNabpK01LLH+LKuQqJYKIUJhbyNf1viY/LZ+XzrxU0iapqFw3mSczWfbyMnb9uAu3sm50/7k75aPL33Y71PBDlRJBURQMFgMe5TzISc5heofpJW1SqWLq1KmYzWYURXFu4eHhbN26lXHjxmEwGIodUxQFjUaDTqcrVubh4UG3bt2ckTQXNldXV0aPHl3Sl3nH4x7szkMzHuLJtU+SdSqLzRM3l7RJl0QVcpVbSo85PQDIOJZRwpaUHtLS0nj//ffJzy8+GenQoUNER0cTExPDBx98gF6vL3ZcRLDb7cXKMjMz+fXXX/n3L++cnBwGDRp0ay7gLqR8dHk8KnjAHRphqwq5yi3F6G7Eq5IXZ/efZclLS7BZ7878LDeTjRs3kpNz6Xwg+fn5DB48GICoqCgMhv/us92/f/9/PvdepDC3kORdyZw9cOcl31KFXOWW03txbzR6DRs+3sCZHWdK2pw7ntTUVLKy/l7pRqMp/m+alpbGc889xyOPPFJsVP7velejb9++N2TnvUbrMa3JOJ7B5PqTyUq8s1YiUoVc5ZbjXckbnwgffCv7EhSlhiFeCYfdgbe390WukH9iNptJTU1lxowZxUbuZcuWdb42Go0XnffvsoMHD+Lm5saMGTOKlT/wwAN4enri6emJXq+nfv2iZ2zjxo3D1dUVDw8P6tSpg81W9OtqxIgReHp64u7u7qx7N1K3f136re+HvdDOtFbTiJ8ff8X36XaiCrnKbaEguwBrllVdC/QK7BgwgojXF/DU4mTyHX+7oP69SpHNZuPcuXMkJiYWK/9nxkSr1ep87enp6TxP+49Zqv7+/syfP5+BAwcWa+ePP/4gPT2d9PR0vLy8ePbZZwF48803WbJkCRkZGaSkpPDdd9+RlZXFF198we7du0lNTSUzM/OybqG7Af9q/vRa2AtxCD91/onvW31P5qnMkjZLFXKV20PUc1Fkncoifn58SZtyx1KQf4bZhYNZ8ucYuukvHlFf4NixY7zwwgucOfO3m0qv1zsF+9/odEXZqu12e7GHoe+99x4tWrSgsLCQzMyLxWjfvn1kZGQwYMAAALRaLRaLBRHB1dWVI0eOkJycjF6v5/nnn6dly5YUFBRc9BD2biO0VSiD9gyi48SOnFh/ggXPLihpk1QhV7n12Avs7P9tP2YfM1W7Vy1pc+5YFtc5hJ+1KFLlBT9/3N09QF/8YabJZMJms2G1Wqlfvz6KoqDX66lUqRK9evXCz8+PsLAwZ32NRkN4eDgNGjS4qL//+7//Izk5GaPReMkVid544w0aNWrk3C9XrhytW7cmMjKSs2fP4u7uTnJyMvn5+axfv574+HgKCgru6hH5BbR6LQ2ea0DL91oSPz+eA3MPlKg96sISKrecw0sPc3LDSVq+2xKj2+VHmvc6P/tm4aY1kuURw2T7/ZRJWoHHrlUEmgx8Pn48Op2OpUuXMmLECADeeustevbsyZAhQ5xtlClThrFjx9KsWTM8PT358ccfcXV1pU+fPri4uODi4kJERASxsbFs27YNKHLDVKxY8SJ7Fi9ezG+//ebcz8rKonr16k5f+8mTJ8nIyECv13Ps2DEcDgfBwcGsW7eO+++//1beqjuGBs81YO37a5n5wEyGHh2KZwXPErFDndmpcss5sf4E3zb9Fq1ei3uwO/41/AnrGEatPrXQm+/un+HXw9pTa8nJsWBRyuFi1FK3vNdNbX/akD6cTU6l+eARxHToREpKCjt27KB9+/YXuVYWL15Mt27dyM7OdpZFRkYSFxeHwWCgWrVqPPPMM3Tq1ImGDRuSmJiI2WzG09OTxYsXEx0dfVNtv5M5tuYYP973I2VqleHJNU/ekj6uNrNTHZGr3HLKNSlH/w392fH9DvLO5XFq0ykO/HGAA78foOe8nsUyJTrsDvLO5Tmn+ItDimYiBrre9aLftGzTW9q+Ofc44Er5skH06NGDgIAAFEVh4sSJ/Pzzz3z//fcsWFDk7x09ejQdOnQodn6jRo0ICgpCo9EQGRnJs88+i6urK/fddx9BQUGICNHR0feUiANUaFaBek/XY8PHG9g4fiN1B9RF73J7P6vqiFzltiMirHxzJWtGr6Fi24rojDrSj6aTk5xD7tlcxHHpz6Teokej02B0N1K2QVkqtatEYN1AytQug0anwWF3oGgU56IO4hDsBXYKsgswe5uve+GLyMhI4uP/fjj77rvv8sYbbwBFLox/PmyEoiiQjIyMYhEjiqLw66+/8uCDD17UfmpqKl5eN3fUfUVsBTgKctGYPaCUruY0depU3nvvPZKTkwkNDeW7776jbt26QFF45BdffMHZs2exWq0YDAYGDBhA9+7defrppzl27Bi+vr4MHDiQESNGMGbMGMaMGQOAh4cHH330ET179vxPdm2ZtMX50NO1jCuNX2pM/WfqY3C9OUm21KRZKnckDpuDuf3ncnjJYVx8XfAO88YSYMHib8HF1wVFW5SrRdEoiEPIPJVJXmoeDpuDvLN5HFt9jMyTRe4AF18XUCD3bC4uvi4ENwrG4GogYVkCuSlF4Y4GNwNhHcIIvy+cag9Xu+qIafXq1bRo0eKi8gv/LxUrVuTIkeILNJvNZvLyLl5hZsiQIUyYMOGybZU0U6dO5euvv0ZRFCZMmOAURigSx7lz5wJF0TIPPfQQH3/8MRs2bGD48OHodDo6d+7s9NuPGTOGX3/9FUVRePTRR3nxxRdvmp1paWnExMSgKAo///wzvXr1wmQysXbt2ovqdurUibS0ND755BOGDBmC1Wp1hlpmZ2fzySef8Mgjj7Bz5070ej2VK1emsLCQY8eO3ZCNx9YcY8XrKzi+5jhuZd2o+nBVogZG4RPhc0Ptqq4VlTsSjU5D12ld//P5IkLqoVRObTzFoT8PoXfVY/G3kHkik1ObTmHLs1E+ujyB9QMxWAyk7E0pSrH7y16WjlhK1HNR1HuqHm5Bbpds/5lnnnG+7ty5M/PmzQMgJSUFPz+/Yr7jC6xYsYLGjRsDxUV9165dl+wjJycHi8Xyn+/BzSAtLY3x48fz119/cerUKR5//HGnMA4YMICff/4ZRVH48ssvmTFjBg8//DBQJJR2ux2NRsPatWuZNm0aGzZs4JNPPiEvLw+NRsObb77JM888g8VioWvXrixbtgxFUejVqxdfffXVddu6ceNGQkNDqVChApGRkdhsNjIzM7FarcUmO6WkpHDo0CG0Wi2NGjUiI6Moz0/58uWpX78+cXFxbNy4kaCgIOx2OzabDaPRSERExA3fzwrNKvDk6ic5vu44q0auYsuXW9j69VYeX/Y45RqXu+H2L4cq5CqlEkVR8An3wSfch5q9a17TOSLC8TXHWfvBWlaNXMXqd1dT+YHK1HumHuWblS/mgz948KDz9dy5c53umjlz5vDss89y7ty5i9q/IBhAsZH5P9v6J9nZ2SUu5Bs3bqRZs2YYDAZCQ0PJzs7GarWSmJjIjz/+SHJyMlu3buW+++4jODjYGY7o5+fndDtZLBbq1KmD2Wzm3LlzLFmyhAYNGuDl5cXKlSupWrUqixYtIj09nby8PAIDA/noo49wd3e/LltTU1PRarVOd5SHhwdWq5XU1FQCAwOd9X766ScqVqxIw4YNAfD19SUnJ4ctW7awdOlSTp06RdOmTenUqZMzlFKv1/PCCy/chDtaRPno8jy+9HEyT2UytcVUfur8E8OOD7tlvnM1jlzlnkFRFCo0r0Cvhb0YcmgIjV9szNFVR5nefjpj3MawdcpWZ91/z6a8wL59+y7b/n333XfJRZcvt6Dy9OnFU/uOGzeOmJgYYmJiCA0NZfjw4QBs2LCBJk2a0Lx5c8aOHeusP2bMGKKiomjQoAHjxo27/IVfgX/76T08PJzT/yMiInB1daV58+bk5+fTpUsXZz1fX1927NjBzp07ycvLo1q1as6JR3369CEiIoLQ0FBmzpzJ6dOn8fDwwGazodPp0Ol0HD9+/JptFBEKT+fgmqfHXmgjPT0dKPrizM3Nxdvbu1j9GTNmkJSURO/evQGYPHkybm5udOjQgaNHjxIcHIxGo2HOnDkkJCSQnp5OREQE7777brEv45vBmR1nsGZYyTuXR8bxW5cBVBVylXsS70retP2oLS+efJFHfnsE70rezHtqHsd/XsqA15uiM/39r/Hpp586Xz/5ZFF4mclkuqhNu91+Sb/3v1PLXuCzzz4rtv/iiy8SGxtLbGwsVapUcboxnn/+eWbOnMnq1auJjY0lPj6erKwsvv32W/766y/Wr1/PV1999Z8m4nh7ezuFEYrE0dvbm6SkpGIzRUWEJk2aOPcnT57Myy+/TNu2bfHz8yMoKMg5Qv/oo4/YuXMnCQkJnDx5ksqVKzvzqVeqVAmHw3FJ19TlyIo9wZlPt1Jxl4UjhxJYs2YNhw8fRq/X4+7uXsytEh8fj9VqxWw2Ex4eDkC1atVYu3YtiYmJ1KpVC7PZTLNmzXB1dUWv12M2mzGbzej1+ku+r/+FnJQcfu/7Oz/e9yN6Fz0Nnm+AT+SN+cmvhCrkKvc8qYdSORdf5CrZ8O6vDE58jZHRf0+yGTZsmPN1dHQ0VapUITQ09KJ2LjUaB/DxufQ/sEajKRbhcoGUlBSOHDnidGNkZGRQvnzRqjT169cnNjYWs9lMUFAQeXl55OXlOYXoWjnQoCEH6tWnYcOGrF27lsLCQo4fP46rqytGo5HAwEDn6DQ+Ph6Hw0HLli2d51erVo1FixaRk5NDhQoV6NixIyJCtWrVGDp0KFWqVEGv1+Pv78/Zs2dxdXUlLCyMZs2aodPpritTo9ajSKg9TW4MGTyEjIwM6tSpQ0FBAQMHDmTYsGHOXyrTp0+nTJky9OrVy3n+uHHjCAsLw8vLi1WrVpGYmIjRaKRq1arOZF+7d+/GaDTSvn37Yr+GevToQZMmTWjYsCFTp04FiiZCxcTE0KxZM6Kjo7kQwFGQXcC277YxPmw8/wv4Hzum7aDZ680YHD+Yjp91vOzn42Zw1bupKIpJUZRNiqLsUBRlj6Ioo/51/CVFUURRFN9bZqWKyk3GYXew7bttTIiYwNIRS6nYtiK1n6xNfHwgf0zdjGGrHzqNttg5ZrOZ3Nxc4uPjL+kj//zzz53uhX8ya9asS/4TBwYGkpqaelH5Tz/9RI8ePZz7F9wYBQUFLFu2jNTUVHQ6ndPHGxERwdNPP31duckdmZk4cnLw8vJi0KBBtGjRgp49e/Lpp5/yTv+pJOxPIj4+ntzcXD744AMMBkMxn/a4ceOoWbMmeXl5jBw5Ej8/PyIjI7nvvvsICwsjJCQEjUbDqFGjEBEqVKjAmjVrmDhxIjqdjuXLl9OkSROio6PZunVrMdv+7WJ6a8ZHBH/QjBMP6Ph2+lSCgoJ488032bFjB7169WLXrl188803uLq68vPPP/P+++8zqG9f0n/9jbSfZ/FkUFm61aqF4nBQu3x5hrZowaBHH6WzlxeV/f2pVqYMjzWvw6tTh9J3Yl/Opp1l9sLZhFYLRRui5emvn6ZKhyo89cxTVKpViYnLJvLQqIfo/2V//Pr40b5Ne6p4VSHSPZJW/VoxL2seMSNj2PfAPoYvGE6b9m2cv64A+vXrR2BgoDOHzU1BRK64UbQmhuv513pgI9Do/H45YDFwDPC9Wlv16tUTFZWS5uCig/J51c9lJCNlcoPJsvnLzfJt029lJCNleofpsunzTTKpwUQZyUjn9qHPhzKr+yzZPWv3f+73zz//lKFDhzr3a9WqJfn5+RfVa9CggcTHxzv3d+/eLe3bt5d27dpJ7969Zdq0aXLgwAGJioqS/Px8yc3NlaioKDl58uQ122I9cVIKz527qDwnr0AmPrNcJj6zXPr27Suurq7i5uYm06ZNk5kzZ0qnTp2cdZs1aybdunUrdn6XLl3E09NTPD09ZeTIkc7yatWqiZubm3h4eMgTTzwhderUkcmTJ0vdunXFzc1N4uLiirXz8ccfS4sWLcTb21sCAwPlxRdflPr168uBhQslecJE8XRxkc61a0vyhImy+/33pUZwsOwbM0aCPD2lQcWKEt+0meyNrCx7IyvLV2WDpYOrm/T29HKWRRqNUtVolGUVK8neyMrS3GKRoQ9VlMrjK4uhjEGqT60uVb6sInpfvVT5vIoYyxvFEGCQsDFh4hLuItWnVpfqU6tL7eG1JYQQGRc8Tv4c+qe0aNBC1q1dJyIiTzzxhKxZs+aie3zy5ElZuXKl9O/f/5rfL2CLXEmnr3TwosrgAmwFGp7fnw3UAo6qQq5SGrDb7PKO/h0ZyUj5Jvob+aP/H/Ku8V35wOsD2T5tuzgcDmfd7ORsObnppGybuk1m95ztFPVTm09J5qnMK/aRey5X0o6mic1qk+TkZHn77bdl0qRJUq9ePSkoKJBjx45JdHT0ReceOHBAGjZseMl2rVardOrUSZKTk2X//v3SqlUr57GmTZvK/v37b+DOnLfd7pD3Ptwg3y+Kv3rl/8iff/4pkZGRoiiKAAKIi4uLU8y7dOkiJpNJNBqN87hOpxONRiNGrVaU82VaEB+t1lmHf5QH6nQSZDCIm8Ui7m5uYjaZxNViEX8/PwkMCBCtVis6nU5efP55OfTjFBno4yPtQ4OlXPlyElwuWOYvmi+Hjh2SDp06yG/zfpOohlHy6uuvSk5BjtSoWUNOp5+WB2Y9IGV8y8jjPC4H5h+Q5ORkqVy5svM6n3jiCYmKipKmTZvKzJkzi92Dmy3k1xR+qCiKFogDwoDPRWSjoihdgFMisuNKvh9FUZ4Gngacfj4VlZJC0Sg0GNyAuElxnFh3gpQ9KVTtXpV2/2uHaxnXYnUtfhYsfhbKRpWl9hO1CW4UzKKhi5gcNRmAsI5h1OxdE1u+jT0/7+HU5qL4dVv+37nEPcp70PrL1gAkJiY63RiKovDZZ5+xffv2Yomwpk+fXsy/C0Wuhgtx7CNGjMDPzw8/Pz8aNGhAo0aNEBFatmxJZGTkDd8fjUbh9f9rdPWKN8D+/fs5cKB4tsDc3FyaNm3K2rVr2bhx40XrlV5YxOKfTxTsQOoloovsgCYggGHDhvHcc8/h7e2Nm7s70dHRREVFkZqayrx58zh16hSxa9fSolF11uTkkGQroGJEZb788ktiYmIwGo2MGTOGxQsWk5udy3vvvIdGo8FgMdB3aF/OTDtDHerQ/uH2hHUIY+LnE4u5xP73v//h6+tLamoqrVu3Jioq6pLJyW4G1zWzU1EUT+A3YCgwGWgnIhmKohwF6ovIFRezU2d2qtwp2AvtFGQVYPIyXfNDKBEhKS6JzFOZnNl5ho2fbiQvtShe3D3YnYjOERhcDejMOsxeZjR6DRs/3UhWYhY9/uhBWJuwq/Rwc7jWmZq7d+/GZrPhcDgICAhwJr3q3LkzWq2WCRMmcOLECRwOBxqNBofDQY8ePdizZw/Hjh1ziu+sWbPo0aMHO3bsQETIyMhg8uTJTh9wRvIZBr/+GWu8mzDo6NdM2bKHg5dIm2swGAgMDCQkJIQDBw5w+vTp/3wPvL298fb2Ji4ujqCgIDw8PAgMDOSHH35g0KBBZGVloSgKR48eJSwkGN3eg5z2dccnsDx//fUXLVq04KOPPqJLly4EBQXRtGlT5+xcvzA/glOCcc9056PxH9HguQYoGoWGDRsyffp0Z7TMP/m///s/Gjdu7EzVEBsby/Tp05kyZco1Xc/VZnZel2vlvOi/DbwJJFPkUjkK2IDjQJkrnau6VlTuJmwFNjm987ScjT8rDrvjknWyTmfJhMgJMpKRkrA84Zbb1Lt3b1EURTQajYSEhEitWrWcxy64LLT/cEdotVopV66cc9/Ly0sqV64sQ4cOFQ8Pj2J1Q0JCZOHCheLi4iJ169YVi8Uijz32mCxcuFBEilw/GzdulNatW0tISIiz31nzV0uFl+dLhZfnS/nnZwiK5iJ3yIWtsr9e8j+sLA9W1l22zrVsGo1GwsLC5O2335aqVatKq1at5JtvvpHw8HApU6aMBAQEiKenp0RFRcmONXOlsYuLuFtcZMyYMXL8+HHx8PCQ2NhYURRFatasKa6urtK8eXPZuHGjlI0oK4qiSAUqSFTVKOnevfslXWJpaWnO+9KkSRPZvfvv5ys327VyLVErfudH4iiKYgbaANtExF9EQkQkBDgJ1BWR//4VqqJSytDqtQTUCMAn3OeyCblcA1zxDPEEIGlr0i2158iRI8yaNQtvb2+WLFlCSkoKBw8edIY4/vHHH+Tl5WGz2XB1LXIjde3alZSUFAAqV66MVqslMzMTHx8f0tPTOXbsGCaTCa1WS3Z2Nm+++SYdOnSgV69eBAYGcuTIEfz8/ICiEfX06dPp2rUr1apVc9plDPo7VDM/6RBoL+/RPZkpxOZUYmuS7bJ1rgWHw8Hx48edoZpubm788MMPhISE0KpVK15//XVee+01EhISeLjv8/Tx8mbEgO78/vvvzl8wL774IjNmzGDHjh189tlnFBYWMmzYMPqM7MP9te8ngghWLF/BL7/8ckmX2COPPEJ0dDRNmzblkUcecd6TN954g+HDh/Pnn3/Spk2bm7MQx5VUvuiLgJrANmAnsBt46xJ1jqI+7FRRuSTvmd+Tnx/6udiD1FvBu+++K35+ftKgQQMRETGZTOLi4iJHjhwpVm/v3r1yPmRY3n77bdHr9QJI9erVpUGDBuLi4iIPPvigiIiMHj1adDqdmEwmad++vfTp00cmTZokRqNRTCaTtGnTxtlufn6+mEwm8fb2lq+//tpZnpZjlWpvLZIKL88X384vicbV57IjaS8vL2ncuLFUqlTphkbknH+AGhER4bwfIiIvvfSSvPLKK879nj17yocPtZC9kZVlw5zPRUQkMTFROnTocNn7fCzjmHR7uJuMZKSc2X3mv79h1wE3OiIXkZ0iUkdEaopIdRF55xJ1QuQq/nEVlXuVwLqBHF5ymNi3Y0k9fHHc+AVEBJv1v49Ek5KSMBqNTp+/0Wi85EzTN954A0VR8PDwID093XnOoUOH2LJlC4WFhc54+EmTJmGz2bDb7XTr1o0+ffowaNAg7HY7999/P5UqVeKXX34BYPny5Tz00EPEx8czZswY54QiTxcDM5+rQj2OEGDRYQy6/ENZnWLn6JGEizJL/hcUm40jCQkknTrFyZMn2bJlC59++ilTpkzB09MTX19fypUrR42yRVNgJs5ZS8uWLRkwYMBF2SqPZR5jYcJC5h2ex9bkrRyNPgrA7pm7b9jOm4GaNEtF5RbT/efuzBswj9XvrWb1u6sp36w8VR6qgsnThDXTyq4Zu0g9lEp+elGkRtPXmtLirRZo9dqrtPw3a4/FsSe/aIHkI0eOUFhYSH5+PhqNplhCqdS9e5k7d65zJLdmzRrGjh3LwIEDyc/Px2QyodFoaN68OfHx8Zw+fRq9Xs8PP/zAq6++CoCXlxe9e/cmLy+PlJQUUlNTKSws5IcffqBPnz5YLBZMJlOx6e7Z82bw9IalPD58JIVb/0ApE4ScTrzoOs6mZuJvyeTfwSgBFsi0Qt4lvue0FEWq/Jt6egPb8nL5SKsjp1t3/KtV49QHH2KqXh1z9WrogoJQFIU/n3uQTBeF6TN+vOS9Hf3XaGYemFmsrNKWSsCdk4pYzUeuonKbyDyZyc7pO9k+dTvnDvw9M9S3ii+hrUIxeZo4u+8s+37dh0d5DxoNa0TdAXWvujhBYUE6+vcrcCTNQZWvbQT4++Pm5sa+ffuoUaMGU6dOdYY4TurXj0HTpuHq6orJZMLV1ZUzZ85QUFBAxYoViY+Px9/fn127dvHWW28xZcoUTCYTSUlJNGjQAJvNhqIoGAwGMjIy8PLyYt26dSQmJlKzZk0aNWpEQUEBQ4YMKbZIQ+rMmXyx6i8m9uhL3p+/k7fgN2xJJ5H0NNBq0SkKOBz079qMGQs3MOqp+0jPzGFlXDyb9h3nxZb+fL4qiYreevYkFyJSNFPRgYJOp8Ps4kJWVhZWq5XHHnuM2bNn0zImhoKsLL7o+yS+p0+Tv2cP+fHxcD6UUevpibFyZVIO76YwJ5v54x/CLnYcDgcOHDjEQb4tnzWn1gDwacynhHuFo1E0LH5wMSeXn+T1/NfRGW/9eFjNR66icofgHuxO01eaEv1yNDlncrDl29DoNbgFuf29qpEIBxccZP3Y9SwetphVo1ZR+8na1H2qLn5V/C7ZrkZTNPIt42Wm+8MdmT3rZ06ePEnFihXp0aMHQ4YMcWYunL5/P2VdLLSK7kDz7u2ZMmUKaWlpFBYWcujQITw8PPj222/x8/Nz5kOpW7cu7dq1480330Sn0zF27FhMJhOhoaHOxZ0jIiIuiv3+J1rXv/O+mzt2xdyxK46sTM49/SgaTy8cRw7h6+ND1eYP4rPlCC9+NgeA5557jhOZC3hy4hJW9unDX3/9xbFjx3jqqafIy8vj6NGjrF+/nqeffpqKFSvStGlTrFYrnp6e/DB9Ov3796fGc4OcfTusVqzx8eTv3k3enj1YDx5ErzexJ8zOltNb0CgatBotCgpaRYtGoyHYNZg+1frQukLRfABrlpWTy0/iXs79toj4taCOyFVU7lBObjzJX+P+Yt9v+3AUOijfrDz1nq5H1e5V0ZnuDAG5VqSwkINr1zPBzZ9d2+OwuXpQ8WwiZ5cvZmfcFnKzs3Fzc8PT05MWLVrQr18/li5dSlZWFn5+fs4FPYYMGeKcIHXixAlcXFzw8fGhb9++fPbZZ1gsFvbv309wcDBBQUF89tlnhIXdvPh9W76NpS8vZdP4TVR7pBrdZ3a/aW1fCXWpNxWVUk5Ocg7bp21n69dbST2UimsZV1qNbkXtJ2vf0ox6t5LM9HTWrFvH5s2bAejfvz/lyt26FXRuBpmnMpnafCppCWnU7lubduPaYfYy35a+VSFXUblLEIdwZMURVo1axfG1x6neszqtx7TGo5zHdS8sfaeQkZGB0Wi8aXnAbwXJe5LJSc4h9q1YTm8/zcOzH6ZSu0q39UtUFXIVlbsMcQhrxqwh9q1YxCH4VvGl5bstqfJQlVI7Qr9TERFGm0djt9pRtAqdJ3emzpN1brsd6sNOFZW7DEWj0Pz15lR+oDIJyxKImxTHL91/wb+GP42HN6bGYzWuK3RR5fLkp+Vjt9oxeZkYtHvQZRfrLmnUFYJUVEop/tX9afRCIwbuHkjXaV1B4I++f/B55c85tvpYSZt3V7Bzxk7gvKAXXnrJvjsBVchVVEo5Gq2GWn1q8ezOZ+k5ryeKVmFay2msfHslDtulF5FWuTaiBkXR+KXGAMUW577TUIVcReUuQVEUIu6P+P/27j04ijpb4Pj3N93peeQxJJDwhoCGiWB4yJsAyZVVQAsUUWsXMW4Jd5UqrVKwrlrLLniVC6uuehddXQsueJX1sVgL6wJqsRdBFCNKIg91CYTHQnhmSCCvySRz7h8zjAlvkknCJL9PVVeYX3dPzplJDr/0dPfhoW0P0f/+/mz6z00sz17OmSNnWjq0qGUzbPSd2heA9n2arnlyY+lCrmmtjBVncefyO7lrxV0czT/Ke5Pfw1/hb+mwolbB2gIAOvbv2MKRXJwu5JrWSmVMy2Dqu1Mp+raIj/79o5YOJ2p99fJXAJTsL6H0YCnHdx4PNxS5VuhCrmmtmGeSh7G/GcuOP++g6Jvzb1KlXd6Ut6dgOkzev/N9Huj5AIMzBuNp7+HZ4c9SXVYd3u6ll14iOzub7OxsevXqxZw5cwDYsmULo0aNYuzYsbzwwgvh7QsLC5k0aRI333wzOTk5jQvyUve4jfSi70euac2vqrRKFiYslJU/X3neumXLlsnIkSNl1KhRF+1kn5WVJampqTJ79mwREVm7dq0MGTJERo8eLdOmTRO/3y/FxcXhbbOyssQ0TfF6vc2S3+U0JMf7779fsrKyxOPxiGEY4unjkRcfe1GcllOS4pNEEWwcnWKmyOiRo8P7Tp48WWJjY8P3RO/atasMGTJEFi5cKKYZ7HrUsWNHERGZOHGiFBUVyZ49e0QpJQ8//PBFc+Ay9yPXhVzT2oBPnvhEnjGekVP7T4XHvF6vDBo0SHw+nxQWFkpmZuZF9584caJs2bJFREQGDx4s+/fvF5Fgp/izrd7Oys3NlfHjx0c+iSswZswYsdlsopSSbt26ybBhw8Tj8YjP55O0tLR6jSdM05TU1FS58cYbxWb7qf2c2+0Wm80mlmWFxzwej9hsNklMTBSn0ylbt24VW6hl3e1Dbq/3+gwYMECuu+46SU5OloyMDElNTRWXyyWrV6+WnJwcMU1T3nrrLcnKypJ77rlH4uLiJCEhoVGFXB9a0bQ2YOAvByK1wu6PdofHcnNzGTNmDJZl0atXL8rKysJt4eo6ceIE+/btY8SIEQD069ePkpISRIKNls+2ejvrnXfeYfr06U2b0AXk5+ezefNmdu/eTY8ePThy5AizZs3i9OnTWJZFbm4uTqeT06dPExMTQ6dOnbjhhhvYtWsXS5YsIT09HZfLxfTp07EsC7fbTXp6OgA1NTVYloXdbqdPnz60a9cOl8uFQlFSXFLv9SkqKuLWW2+ltLSUKVOmYLPZqK6uZsKECXz77bc4HA5WrFhBXl4e06dPJykpiZqamgu+9ldKF3JNawOObT8GQNdhXcNjXq+XxMTE8GO3243XG+xgNHPmTBwOB0opUlJSKCgoIC0tjczMTPLy8hg4cCA2m41Vq1YxdOhQlFLhphSLFy8mJycHwzCIiYnB6XSilEIphWEY4YI4c+bMiOb48ssv0759ewoKCrjjjjsIBAJUVlYSCATw+Xzk5uaSmJjIhg0b8Pv9uN1u9u7di2EYbNq0ibvvvhubzUZ+fj6madKnTx+Ki4ux2WwcOHAAEaG8vBy3280jjzxC+8T2GBgc9R3l3nvvDcdRWVlJfn4+w4YNY/369UyePBkRYejQoaSkpFBZWUlFRQUZGRk88cQTvPbaa8TFxVFSUtLg3HUh17Q2QALBeyqZzuBdOc7es7tu8SgtLSUpKYl9+/axdOnSejPE2tpaCgsLeeqpp9i5cyeGYdS7r4vNZsPn84U75ogIdrudHj161LtPeSAQ4PnnnyclJQW/P3KnRPqrfez58Qcs02BX7hYC5WdQSvHd559hGAZerxev10ttbS1z584Nx3X77bfTpUsXli9fzqJFi6iurqagYA/jJ45n6w9bOXnqJM54J8pQmA6TM2Vn2PbdNrrbuiOHhQABTlWeCv8Fsnv3bnr37s3XX39NZWUlvXv3ZtCgQXz44YccOnSIzz//HIfDgcfjoaioCBFhwoQJVFRUEB/f8Mv/dSHXtDag86Bgu7ejeUcpLi5m4cKFbNy4kc2bN+P3+zl48CBxcXHY7fbwmRVOp5OOHYPnTp+dXS9YsADLslixYkV4Rm0YRrjH59n9IDgztaxgd6P77rsvvM2TTz4JEG5cEQl/eiiHqqNFlHq9/PiPdXy3aQOBQAC39zgnjh3l7y88x3f/9ymBmhp27drF/PnzOXLkCDNmzODw4cO4XC5u6jcCm5icOH6cnvYsXH1dSI1QfrqcmJQYaqwaUFBWWsbH6z4mMykTI8bAV+0jLS0NCB5WyszMxOFw8OWXX+L1etm/fz+vvPIK/fv3Z+7cudTW1jJnzhw8Hg/79u3D6XRSUVHBBx98wLJlyxr2AlzqAHqkF/1hp6a1jNqaWlngWiBrH10rR48elXnz5smSJUtk6dKl4TM6tm7dKnl5edKhQwdRSklKSookJycLIIZhSHx8vKSlpUl6erokJSVJTEyMABITEyMJCQnndbE3TTO8Tb9+/cJnbZimKUlJSTJjxoyI5Lbyx69k2LOrZfEv3xSFksJH3NK7HWIo5MBjcXJ9ok2GdzFlcEdTOrqCH1D+Iq2duEyb5N85XBRKxneZIgsG/ElMTDEx5b96L5Zuju7S2ewigNiwSQLBHA0MUSgxbIaMGjVK0tLS5LbbbgvH06tXL+nQoYNkZ2fLmjVrRERk8uTJYrfbw6/juHHjpKysLLxPVlZWoz7s1Hc/1LQ2wGbY6JnVk+9Xfs/op0czf/788LoHH3yw3rbxCfF4vV4sy6o3a66uriY5OZmSkhJuuukm1q9fj1KK2tpaJkyYwMqVKwmc0zXZZrMRExNDUVERNaFemfPmzWPBggWcOnXqgrGKCP5yP1WlVVSfqcZ3xlfva3VZ/bEPt+znhtJq/lkToLfVk+tePYAAbmLp/4oC4hl36ucUUsguPieGWtYUBBjICF5flYGbf/Jp0So+LVqFIIx0jCTGX0OJ/xTlteXBoBS4E+PI6JrB+0vep/Pgzvx23m9Zt24d5eXl+Hw+ysvLiY2NpbCw8LycVq9efcn357PPPrvk+svR9yPXtDbi4BcHefuWtzHtJr3G9WJAzgA8kz3h9Q9+tYvKr3/F39/aTtm2MnDEY/NXEqgNFuC4uDi6d+9Ou3btsCyLjRs3YrfbARg+fDi5ubkEAgGUUlRXVxPrjKW8spzOHTpjmRZlFWWUlJWQ6EqkpKKEIV2G8OiAR/GV+qgqrcJ32oev1IfvtC98TP9yrDiLansVZ0wHPdrFE5fgwB5n4Eh2YHe7sBKc2BPsWPEW9vg6X+Os88ZMp3nN3s9dN5bQNC3s5I8n2fjMRna+t5OUG1OYtWMWAL6qGr4Zm8n//Kw7W0/vZsdrO87b1zRMJCCkJadx0HuQipoK4ow4TGUSTzyHaw4ToP6MXKEQzq8xDhzYDTudnZ15fNDjJCQlYE+wY3fbcbgdwX+HlvOKcLwVLMSxVtR2RrpaurGEpmlhHdI7MPXdqXS6qRPr/2M9i9yL8Ff6CfgDwG302Ao9yKCEEv7Fv4Bg0TUwqKqtYpgxjJEykj/W/hGX4aJrfFeOVR0jNiGWwPGfirhhM+jeqTsPTHmAZ157BsNmgAKXy8Ubb7zBtGnTWugVaJ30jFzT2iDfGR+bntuEv8IfnN2GZrhWnIkV78CKtS44Q7aZ+kS3lqBn5Jqmncceb+eW393S0mFoEaL/e9U0TYtyupBrmqZFOV3INU3Topwu5JqmaVFOF3JN07Qopwu5pmlalNOFXNM0LcrpQq5pmhblmvXKTqXUCeBAs33Dn3QATrbA921ubSVP0Lm2Rm0lT7j6XHuKSPLFVjZrIW8pSqlvLnV5a2vRVvIEnWtr1FbyhMjnqg+taJqmRTldyDVN06JcWynkb7Z0AM2kreQJOtfWqK3kCRHOtU0cI9c0TWvN2sqMXNM0rdXShVzTNC3KtapCrpS6Rym1SykVUEoNqTN+i1LqW6XUjtDXmy+w79+UUjubN+KGu9pclVIupdQapdSPof0WtVz0V64h76lSanBofI9S6g/qWu2oe45L5NpeKbVBKVWmlHr1nH1+Ecp1u1LqY6VUh+aP/Oo1MFdLKfWmUmp36Od4avNHfnUakmedba64JrWqQg7sBO4CNp0zfhKYJCIZwAPA23VXKqXuAsqaJcLIaUiuL4pIOjAIyFRKTWyWSBunIXm+DvwKSAstE5ohzki4WK5VwG+AJ+oOKqVM4L+BfxOR/sB24JFmiDMSrirXkF8Dx0WkD9AX2NikEUZGQ/K86prUqlq9icgPAOdOwEQkr87DXYBDKWUXEZ9SKg6YTfAX/4PmirWxGpBrBbAhtE21Umob0K2Zwm2wq80TSAISRGRLaL//Be4E1jVHvI1xiVzLgc1KqevP2UWFllilVDGQAOxphlAbrQG5AjwIpIe2CxAFV4E2JM+G1KTWNiO/ElOBPBHxhR4/C/weqGi5kJrMubkCoJRqB0wC/tESQTWBunl2BQ7VWXcoNNbqiIgfmAXsAIoIzlKXtmhQTST0MwvwrFJqm1LqL0qpji0ZUxO66poUdTNypdR6oNMFVv1aRFZfZt9+wO+AW0OPBwLXi8jjSqnUCIfaaJHMtc64CbwL/EFECiMVa2NEOM8LHQ+/Zs6xbUyuF3iuGIKFfBBQCCwGngaea2yckRDJXAnWqm7AFyIyWyk1G3gRuL+RYTZahN/TgTSgJkVdIReRnzVkP6VUN+CvQI6I7A0NjwQGK6X2E3wtUpRSn4lIdiRibawI53rWm0CBiLzSyPAiJsJ5HqL+IaNuBGer14SG5noRA0PPuRdAKfUB8FQEn79RIpxrMcEZ6l9Dj/8CzIjg8zdYhPNsUE1qE4dWQn+WrQGeFpEvzo6LyOsi0kVEUoHRwO5rpYg31MVyDa17DnADjzV/ZJF1iff0CHBGKTUidLZKDnC1s79ocRjoq5Q6e1e8W4AfWjCeJiPBKxc/ArJDQ+OA71ssoCbS4JokIq1mAaYQnJH5gGPAJ6HxuUA5kF9nSTln31RgZ0vn0FS5EpyZCsFf9LPjM1s6j6Z4T4EhBM8W2Au8SugK5mt9uViuoXX7AS/BMxkOAX1D4w+H3tPtBAtd+5bOowlz7Unw7I/tBD/f6dHSeTRFnnXWX3FN0pfoa5qmRbk2cWhF0zStNdOFXNM0LcrpQq5pmhbldCHXNE2LcrqQa5qmRTldyDVN06KcLuSapmlR7v8BSXR8Y5GINwUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting underused PRECINCTS\n",
    "for p in range (nPrecincts) :\n",
    "    if precinctUse[p] < 0.8 and isSkippedPrecinct[p] == 0 and vtdPop[p] > 0: #ignore suppressed precincts\n",
    "        print(p,precinctUse[p], vtdPop[p],\"pop,GOP\",vtdGOP[p])\n",
    "        pU = round(precinctUse[p],3)\n",
    "        tractX = vtdGeom[p].centroid.x\n",
    "        tractY = vtdGeom[p].centroid.y        \n",
    "        # print(t, ratio,\"(\",tractX,tractY,\")\",HDvGOP[t], \"t, pop/target,(x,y), pctR\")\n",
    "        plt.text(vtdGeom[p].centroid.x, vtdGeom[p].centroid.y,pU, fontsize=9)\n",
    "        if notPolyVTD[p] == 0 :\n",
    "            x,y = vtdGeom[p].exterior.xy\n",
    "            plt.plot(x,y)\n",
    "        else :\n",
    "            for geom in vtdGeom[p].geoms:\n",
    "                x,y = geom.exterior.xy\n",
    "                plt.plot(x,y)\n",
    "\n",
    "x,y = MAP.exterior.xy\n",
    "plt.plot(x,y,c=\"purple\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 350,
   "id": "37f47a77-d58e-4b4c-be60-676819128e21",
   "metadata": {},
   "outputs": [],
   "source": [
    "# (OPTIONAL) IF WE STOPPED AND RESTARTED, read the data back in:  #NEED TO UPDATE THIS W/ANGLES, RADII\n",
    "import pandas as pd\n",
    "infilename = \"FL_nD28tol0.01nW4.csv\"\n",
    "df2 = pd.read_csv(\"state_HD_output/\"+infilename)\n",
    "HDvPop = df2[\"HD-pop\"]\n",
    "HDvHisp = df2[\"HDvHisp\"]\n",
    "HDvGOP = df2['HDvGOP']\n",
    "HDweight = df2['HDwt']\n",
    "HDarea = df2['HDarea']\n",
    "tractLoopCounter = df2['Loops']\n",
    "tractPop = df2['tractPop']\n",
    "tractCPx = df2['centroid x']\n",
    "tractCPy = df2['centroid y']\n",
    "tractUse = df2['tractUse']\n",
    "# nearEdge = df2['nearEdge']   #add this back in, PLEASE\n",
    "df2.head()\n",
    "nTracts = len(tractPop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "e9b2c0c0-fb53-44e5-9155-1963d4833ee8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "750596.7418101031 0.1131774380110593 0.0001361943772 0.0400616118781349 0.7450137754374908\n"
     ]
    }
   ],
   "source": [
    "#  HERE'S A BLOCK TO OVERWRITE THE REDONE DATA\n",
    "for r in range(nRedos):\n",
    "    t = redo[r]\n",
    "    HDvPop[t] = redoHDvPop[r]\n",
    "    HDvGOP[t] = redoHDvGOP[r]\n",
    "    tractArea[t] = redoHDarea[r]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "c80e0880-6811-4408-b847-6d70bd2546ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt   #SKIP THIS BLOCK IF STARTING FROM FIRST BLOCK\n",
    "from scipy.stats import norm\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "c8f73bb9-e36b-41c7-9220-1ec09169aa3e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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epk37grS000gZisViwWYLpW/MfcTE/DfzFv5mFyh9LDmvF8sSw6B9Lssu0f6BvDLGeom+xIXT5ORkUi0WLF4v0mIhOTkZOHex8+3Zb3LVsSrc0LnIj6asKAWqRCby2LmxVAyvyOz/zs5Tq07Tal9WXdwwtmcpx3gwjO2FkshNcy12+wOZfcEdjhkYxrcYhklkZAWSk5PR9Y5oWhuACybwDF10nZCQELxeLyEhIXS5jF4szTWNqQ5HrmvkbXWdkLCwzBp5W/97Hdr6D7adFsxrV2Kf141Bfw3i1bteo1xYuVzHoijFSYlM5BUjKhJiCaFp1aaF+r663gCbLQS324PNZkXXGxTK+xrGCn8r2ovbnYZhrGDEiEFoWvRlH8sChElfcSNMysuuzTXXtEsm8AwtNI1pDgcrDYO2uk4L/36rlpqU+lQQUh3cXWFyqff5fOIXDGs/jCfbPUmF8AqXGZWiBLcSmchf7PwiHaZ1oOO0jrx3y3t0rNWxUN5X0+ricDyOYWxH1xsUWllF19ths9lwu9Ow2ULR9Xa52m+1aWIaBhUiIzmanEwHXWeZYSA9HkKkRHo8LDMM2hZgl8QWmpaZwDN08vdt5283Zb6x8do3k5hz/DteNl7mdfN1hrYbyrD2w6gUUanA4lKUIkVKWWiP1q1by6Limz++kde8cY0UcUK+tuw16U53BzqkAuV0rpHx8ZOl07kmV9uvcjrltRERsqbFIquBrCGErG2zyRlTpsjqEREy0mqV1SMi5Aqns4Ajv7DlTqecEB8vl2d5/7V/r5V9v+griUOWiS8jRywcIQ+fPhyQ+BQlPwGr5EVyq5CFOLN8dHS0XLVqVaG936WkuFK475v7mLdtHlFVo5jQYwLd6nUr8d3aTHMlr8f9j5ULfyTd6+vqJ/H1c+k/aBB9Y2JYZhh00vUCbY1fqY3/bOSVpa/w5aYvKRVaisHRgxneYThXlbkq0KEpyhURQqyWUuZYCy3RiRx8n0i+3fotT85/kr0pe2lZrSWv3PgKN9W/qdgkdNPcjmFsRtevR9P+XZc3zV2Z5R44jN3eB+k6TSVvChJIz7Jtrz59mDZ7dmGFniebD2/mlaWv8NnvnxFmDWNg64E80/EZapStEejQFOWyqESeS2fTzvLFpi948ZcX2X9yP/Ur1efNm96kV8NegQ4tT0xzO3Z7QpYujyOyJfPzu0Q+8EApEhPfw+v1EiY8NLq6In/v+ytz+wcHDWLc5MmBOJUrtj15O/HL4pm5fiYhlhAeafUIz3V8jmvKXxPo0BQlVy6VyItHkzMfRIRG8GCLB/lz6J98euenhIeE0/vz3oxePJr8/mdnmodISNiAaR7K1+NeiGFs9nd59PrvQN183vrsXSIPHgzBV00JxyWrcE1jnbCwMIQQhIWFcXdMTIHHnN8aRDZgeu/pbHtiG/2b9WfK6ilc+/a1DJo3iN3Hdwc6PEXJM5XIz2Oz2ugX1Q9zgEm/pv142XiZ2z+/nSNnjuTL8U3zEHb7T4watQa7/acCT+a6fr3/DlSL/w7U689b3yDLeivVqlUHrgeuASL5fsEWut/1CB27d2fM22/TpgjWxHOrXsV6TL19Kjue2MEjrR5h+rrpNHinAY989wg7j+4MdHiKcsVUIs9BGVsZZt4xk7d7vs2CnQto8X4L1h9cn+fjGsZBXC43Ho8blysNwzj4r21M8x8SEtZimv/k+f00rQEOxwjGjLnrX2UVgI0bzxIV1ZaOHdvzwAN30bJlNEJk3MIvAMnMz75lvsPB0GHDLnt8laKodoXavHfre+x8cieDowfz8YaPaTSpEQ/MeYBtydsCHZ6iXDZVI8+FtX+v5bbPbuPgqYN0qtWJOD2OrrW7XtFdofffv5xPPtkOpAJupky5kdjYc61k0/wHu30ebrcXm82Cw9ELTcve28I092AYu9D1unkacTEx8Q8GDlxGxrgrQpQlJOQkaWlLgO34+qpIQsUWkCexWq3EjRnDcyNGXPF7FkV/n/yb8c7xvL/qfVweF/c0vYeRnUfSuErjQIemKICqkeeLltVbsvLRlTzf6Xk2H9nMDTNuoMYbNRjw7QCOnj2a6+MkJu7lk08OAxWAakA5kpPPZNvGMA7gdnv9NWsvSUlbSUhYgWkeADKGz/2QUaMWYLd/mKex0GfNyj5wl5Qp/iTuAWoAVWnRojER4emZE0t0LQITS+S36mWr88ZNb7Br6C6e1p7m2y3f0vS9pvz36/+y8Z+NgQ5PUS5JJfJcqlG2BmNvHMuuobv4qPdH2Ova+Xjjx7Sc0pLFuxfn6hizZh3kXMlCANVYuTIc00zN3EbXa2CzWbBaBSEhgmnT1jFq1DLs9i8xzQMYxq7zhs89l4xNcycJCfMxzdzVe/v2Pf/O0mP4kjhAOFCR9u1b8pPDQdyYMfzkcOR6gKxgdFWZqxjXfRy7h+1mRKcRzN8+n2bvN+OuL+/i90O/Bzo8RcmRKq3kgXOvk5jZMRw4eYC9/7eXyFKRF90+MXEvAwdmrbOXRYgKhIeXxeGogaaFA77yimEc4K+/jjF16lo8HonFYqNbtwb07VuDYcNmZelOOAAIJylpDdOnzyU93eNf/hSadu0lzyEx8Q9mzdpFixZVSUk5zocfziQtLQ2AkJBjLFkyDk1rdqXfoqB29OxRJi6fyMTlEznlPsV/mvyHl7u+zPVVrr/0zoqSj1Q/8gL2w/YfuPXTW+lSuwt1KtQhzBpGREgET2lPUbvCv+vXzz23nQkT/sLrDcE31E0lrFYbY8ZUYsSIitm2Nc0D2O1f4nJZ8HorYbEIwsKsTJx4PcnJx9D1ukA4dvs8UlP3IeV+AKxWC2PG9GbEiJsv+3xMcxtJSYuA08TEdLvsJL7GNFlhGLTTdVoVk9b70bNHed35Om+teIszaWe4p+k9jOoySiV0pdCoRF7APF4P98++n9UHVuP2uDmWeowUVwoPtXiIab2nXXAf00whKSmZadNceDyh2GwiW4s8+7YHiItbz8KFR/F6wWoVjBnTDF2v4m+1n2Lq1C14PCeBrQgB4eG5b5HnpzWmSX+7PXO43JkOR7FJ5gBHzhzhdefrvLPyHZXQlUKlEnkhc6W7uPqNqwkLCWPHEzuICI3IcVvTTMUwzqLrERdM4ue2O4zd7sjsyTJxYguGDfsVt9tLSIhASvB4JFbraR5+uAYxMa3zJYlnnYxC01pecvvJCQm8MWoUXo8Hq9XK/40Zw+Bi1sMF/p3Q/9v0v7zU5SWV0JUCoxJ5AGSUW/6v/f/xxk1v5MsxTfMwhvEPkZEVmTVrDwsX/p7ZQn/00euoVasMul7jX10Vsx9jN4axE12/Fk2rc4n3W4vdHoPLdRKLJZ13300gNrb/RffJaJFnTARR3Frk58ua0M+mn+X+ZvfzcteXqVcxd9P+KUpuXSqRX3I8ciFEOLAECPNv/7WU8mUhRAvgfXzdG9KBx6SUK/Ml6iCX4koB4PrK+ddC07QqQFns9r9xucLxei1YLBKbzUJMTMOLJnDwJXG7/f0sF0kHXTSZG8YKXK6TeL2H8Xph8ODHgHRiYx/KcZ9WmsZMh6PY1chzUrlUZRK6JfB0h6d5bdlrTPptEp9u/JSHWzzMqK6jqFmuZqBDVEqI3Ews4QJulFKeEkKEAsuEEPOB0cD/pJTzhRC3AOMAveBCDQ77UvYx7MdhtK7emodbPnzRbU3Ti2F40XULmnbpnqBJSadJTZVIWQGLpRXR0adp1aoKUOYCxz6AYexD12sCqcTF/YjL5cbrFf5uizsvmsgjI6sA7szXXq+XIUOeJiqqCZrWNsf9WmlasU/g56tcqjLje4znKe0p4pfGM2X1FGasn8Gg6EGM6DRCDZ+rFLhLJnL/oOan/C9D/Q/pf2RMklgeOFAQAQabXp/24p/T/zCu+ziavNeErclbaRjZkP7N+hPbOpaqpasCviRut7txu8FmA4fDhqZZME0wDNB1yJoPTTONadPSyKiEWa3lWL8+lNWr3Uyf/ic332yhWrV0YmJqAi7s9m9wuz1YrW6E2E9amgev19eN0TdLUM41dNPcxLBhHyDlVcCJzOVer8Qwll00kZdk1ctW551b3mF4h+GMWTKGSSsnMXXNVJ5o+wTPdHjmkt1TFeVK5eqGICGEVQixDjgE/CylXAEMA8YLIfYCE4ALXtUSQsQKIVYJIVYdPnw4f6IuwjJu239gzgNsTd4KQK3ytRi1aBTXTbqO+dvn45W+lrjbDR4PuN1gGF5ME+x2GDXK9zXrsCaGkYbHYwVKIYSNli1DSU+XeDzgcnmYM+cU779/FF3/laSkbbjdHjweSVraKdzudH8SF3TrVj8XZZX1uN1pSFkRIephsYRisdgIC4tA1zsV4HeveKhdoTYf3P4Bm4ds5o7r7mDcr+Oo93Y9/mf8L7Pspij5KVeJXErpkVK2AGoCbYUQTYHBwP9JKa8B/g/4MId9E6WU0VLK6CpVquRT2EXXrw//ivGAwZd3fcncfnNJG5XGz/1/ZuPgjVQIr8Atn95C68TWlIlahKX5l1iuXovNBrpuwTA4L7n7jmmasHJlKFKGIEQZQkNLM2BABWw2AXjx3Y1pBcridocBYdhsVqxWQWhomczRDcPCQoiL63nJC5263hybLRSr1UJ4eE0mT57C2LGjcDjmqNb4ZWgQ2YCP7/yYjYM30r1ed+IWx1H3rbq8tuw1TrtPBzo8pRi57F4rQoiXgdPAKKCClFIKXzP0hJSy3MX2LSm9VnKSmp7KJxs+4Yn5T3A2/Wy2dQvuX0CZQ93RdUhLAyGgVCnfujNn8I8R7vtZWSywbJkATjNs2F5WrjxFxkiFFstxYmPL0rJlWZKTT2XWyM9N+Jy7HhWmuQnDWI+uN0fTmuTPN6CEW31gNS8ZL/HD9h+4qvRVvND5BWJbxxIeknPXU0WBfOh+KISoAqRJKY8LISKABcBrwHhgsJTSEELYgXFSytYXO1ZJT+QZjp49yvJ9y6lSqgptP/C1cG+seyNjGzjo2lXiv0OejFEJL6RLF3j11VSSko7x4Yd/k54uEUIixG683tPYbBYWLboJTaua67hMcxuGsQldb4KmNczDGSoX49zr5MVfXmTR7kXULFeTUV1G8VCLhwi1hgY6NKWIynP3Q6A6MEMIYcVXivlSSjlPCHEceEsIEYJvTNbY/Ai4JKgUUYlbGtwCwPTe03no24foXq87SUke0tIsZLSuL2bLFi+6fpC0NAtWa1kGDgzn4MH9zJnj+8jucnlJStoJeDJ7r2ha9RyPZ5rbsNtHZ+me+JJK5gWkwzUd+OWBX/hl1y+M/GUkA+cN5LVfXyOuaxz3Rt2L1WINdIhKkLlkjVxKuUFK2VJK2UxK2VRKOdq/fJmUsrWUsrmUsp2UcnXBh1v8PNjiQRpUasBH6z5ic8QUqL6a7NMdw4WSeo0aZ3G7bUjpIT3dy8GDFqpVy77dwYNnsNtnM2rUcuz22Zjm3znGYRibzpsSblM+nJ1yMTfWvRHnw06+v/d7yoeVJ2ZODE0nN+WrTV/hld5Ah6cEETWMbRFwT9N72Jq8lcXlh8C9t+Hrug/nenn66uIZ7rsP2rd3+7c7BqTy3Xf/0LJlDWw2K0II/7RtoZm9V9xuX8s8J7re5Lwp4XJXF09M/ISbbupHYuInV3DmihCCWxrcwqrYVXx999dYhIX/fP0fWk1pxdytc/N9vlileFK36BcRh04fImpyFCkn00kdvRWolLmubVsXJ0+eQQgrQ4eWIjbWhmm66dRpF17vuZ/f9de7qVLlCKmpLgYMuJaoqLLY7bNxuz3YbFYcjjsuWV65nBp5YuInDBw4LPP1lCkTiY2974rOX/HxeD18/vvnvGy8zM5jO2l3dTvG3jgWe137Fc1IpRQPaqyVILHu4DpaTmnJ0EYTSHz4Ps6etSBEKG3awMqVrsztLBbB5MlliY0tRdeue1iy5Cy+mno6cBLYD5wlLMzCokXdgfRc1civxE039WPBgoWZr3v06MZPP32Gaa7AMJag613QtHb5+p4lRZonjRnrZzB68Wj2puyla+2ujL1xLJ1qqX78JZGa6i1IZNREoxpWYOLEUoSGHkeIw6xadYJzNXKB1yt57LET3HFHCocPZ1wUS8d3O70NqANE4HZ7MYx/0LTqjBjRJt+SuGn+QULCp5jmH/Tt2yvbur59e5GYOI2uXXvw4oujsdtvxTRX5Mv7ljSh1lAeafUI25/Yzjs3v8PW5K10nt6Znh/3ZNUB1RhSslMt8iLCle6i2fvN2H18N1W9TTkw/j28pyoihBUpS/HvrogZ/4OP40viGX0WJXCI0NCjLF7c3T/YVv4wzT+w25/B7U7DZgvF4RjPxo1rmTVrHn379iIqqj5dutxEenoa4EEIycCBjzJ58qR8i6GkOpN2hndXvstrv75G8tlk+lzXh9H6aKKuigp0aEohUC3yIBEWEsYvMb/w3yb/ZZ9cg6XjdKxWCA/38uyz4Vx/vRUhJL4fWUZP0BB8w9xk3FCS8U/Zi5RlSUr6G9PM/eTQl2IY63C70/w9W9IwjHXExt7HTz99RmzsfRjGUrzejDtNXUjpZvr0DzCzjjVwHtNcQULChBLRct9omsxISGDjRb4fOSkVWopnOj7Dn0P/ZLQ+ml92/ULz95vTb1Y/tiVvK4BolaAipSy0R+vWraVyaf2/6S8tcRY5cOx86XSeyVw+aFCKFOKwhIzHEQnJEnZK+F3CBv/XxRK+kzBX2mxzpdOZnKd4nM4tMj7+Gzllyg8yIuIWabV2lxERt0inc9N52y2XERFVpBC2jO420mq1yvj4+ByO69veai0vIyKqSKdzeZ7iLMo2OJ2ya0SE7GC1yq4REXKD05mn4yWfSZYjFo6QpV4pJS3/s8iH5jwkdx3blT/BKkUOsEpeJLeqFnkRNOmWSZQJK8PZJp+haedmGIqJCSc83NcV0WqFLl1CsNnc+FrAGS10AZwhY/h4t9vCuHE7MM0DJCSswDQvb5BK09yK3T6aUaM+Z9iwj5k48XHGjHkQh2M8mtY427aa1g6HYy4DBz5KWFgYVqsVm82GrusXPLZhLMXtduPxeHC73RjG0suKLZisMQzS3G68Hg9pbjdrMgbSuUKVIioRb49n19BdDG03lE83fkrDdxry2PePsT9lf/4ErQSN3NzZqRSyEEsIp9ynqFuhbrblmhaKw1Eew0hD10PRtFBMM5ykpBCmTv0Hjwd8SdyWZS833367l7lzf0VKL2FhITgcd6NpNXIVi2H8ke1GoeTkVEaMuDfH7TWtHZrWjpiY+zAMA13X0bKMx2uav2EYTnS9A7reGZvNljnHp653zv03Kci00nVCbbbM2ZNa5fDP7XJVLV2VN256g6e1pxm7ZCxT10xl+rrpPBb9GM91ei5z2GSleFMXO4uglftX0u6Ddky7fRoPtcx5Rp6sTPMMSUnHWLPmKCtXHvEvlfh6tJwG/gR83RfHju3IiBG56xaY0SLPfut+o8s+J9+xfsNu75vlYukswIthLEXXOwdFV8WNpskaw6CVrhN1mRNo5GXf3Np1bBejl4wmaX0SESERDG03lOEdhlMxomKBvJ9SOC51sVPVyIuglNQUWWVcFdlqSiu57ci2y9rX6TwuLZZfJDj8j/kSvpUwQcIEGRr6hnQ691/mMX01cqdzy2Xtd774+InSaq0moYq0WqvJ+PiJF3nP1TI+/l3pdK7O03vmpw1Op+wSESE1q1V2yYc6d0HacniLvOfreyRxyPIJ5eWYxWNkSmpKoMNSrhCqRh58yoaV5a2eb7Hm7zW0SmzFin2579GhaeUZPrwmvu6Ivvq51erGYqlISEgZJk26KddllXPHbMSIEXfkuiVumutJSJiGaa7PtlzXO/jHObf6ZynqkMP+a7Db72PUqNex2+/DNNdcVrwFJWudOz0f6twFqVHlRnzW9zPWD1qPXkdn1KJR1H2rLhOcEziTdibQ4Sn57WJZPr8fqkV+eVbtXyVDR4dK4pCvLHnlsvadMmWv7NFjlZwyZa90Og/J+PgN0uk8JKWU0uncL+PjV2S2zJ3OPTI+3pBO5548x+x0rpMREe2l1dpaRkS0l07nuvPWr5Tx8ROl07kyx2PEx78rrdZ6EupIq/VaGR//bp7jyg8ZLfIOQdAiP9+KfSvkTTNvksQhq0+oLietmCRT01IDHZaSS1yiRa4SeRG3YMcCSRyy0muV5MGTBy+5vdOZIuPj90mn88Ifo53O/TIi4h1ptU6UERHvyClTVsuIiDhptb4oIyLi8pzM4+M/lFZrawktpdUaLePjP7zsYzidq2VExHXSar1WRkRcl6vyitP5m4yPf1s6nb9dSdi5tsHplB/FxwdVEs9q8e7FsvO0zpI4ZK03a8kPVn8g0zxpgQ5LuQSVyIuBSSsmSREnZIO3G8ile5ZKr9d7we2czhQZEbFSWq3LZUTEysxk7nQelfHxO6TTeVQOGvSLFOJNCW9Kq3Wi7NHjY2m1vihhpLRaX5Tx8UaeYj3XIo++YIs898f5d43c6XTKhPh46TwviTqdv8mIiHrSar1GRkTUK/BkHuy8Xq9csGOBbDu1rSQO2fCdhvKrTV/l+HulBN6lErnqfhgEhrQdQsPIhtz7zb10nt6Z6ytfz3+a/Ie7Gt9FkypNMkfFM4wU3G6vf85PL4aRAqRjt/+G2+0lJETg8RxB+jsqhYRY6Nv3epYu3ZHZK0XX6+YcSC5oWnMcjvcxjNXoems0rfkVHqcVmtYq87VpmvSw2zO7Ki5wODK7NRqG6b/j1OOf69RE03K+wF/SCSHofm13utXrxndbv2PkLyO5+6u7ia4Rzav2V7HXswc6ROUyqYudQaL7td3ZM2wP79/6PlVLV2X04tFETY6i8vjK/LTjJwB0vRw2mwWrFWw2C7peDsM4miW5SzyeMKAsQpTioYdaEhvbCofjIcaM6YbD8RCaVivPsWpac0aMePiKk/iFLDaMbDcPLc5yoVHXtcyLqFar4K+/9mCav7HCNJmQkMCKK7glviQQQtD7ut6sH7Sej3p/xKHTh+g2sxvdZ3Zn9QE1T0wwUf3Ig9SBkweYv30+ryx9hcqlKrPy0ZUAmOZJDCMFXS+HppXFNI9la5FLeRyPx43NZsHh6JGvg2oVpIu1yE1zNUlJX3Pw4EHmz/+JtDQvViEpLY7i8Xiw2Wx8v2gR7Qqo73ZxkZqeyvur3mfskrEkn03m7sZ3M/bGsTSMVFP+BZoaj7yYm7RyEk/Mf4JVj66idY0Lz31tmscwjKPoeiV845MfRNerBU0Sz2CaJosNg65Z7hY1zdXY7f1wuSxAGF7vcUAQyglsHM+c/fThQYN5e/J7gQs+iKS4Unjd+Tqvm6+Tmp7KgJYDeKnrS1xd7upAh1ZiqdEPi7n+zfpTKrQU7696P8dtNm48hmEcZOPGY2haFUaMiAq6JA6gaRrPjxiR7ZZ/wzBxuSx4vTXweisDkQB4CAdE5niQniu4HPSbafJmQgK/lbDSTLmwcvzvhv/x59A/eazNY0xfN53679Tn+YXPc+zssUCHp1yAapEXA49+9yif/v4pB546QPnw8tnWJSb+ycCBW8HfNp0ypRFRUQLD2IGu10fT8nZxM9BMczVdugwkPb08IBAiFSH+BiR4zxIiTmINDcNhzEfT2ub6uL+ZJndkKeXMdjhoU0JLM7uO7eIl4yU+2fAJFcIrMLLzSIa0HUJ4SPild1byhWqRlwA31b+JM2ln+OqPrwAwzRMMHryNwYN38uGHB/Alcd/jww83Yre/y6hR32O3v4tp7gpk6Hmmaa15990XCA21YrEIwsPLM3z4k3Tr1o3hz/4fca+MznUSX26ajEtIYLlpsuy8i6vLivBdnAWtbsW6zLxjJmsHrqVdzXYM/3k4jSY1Yub6mZkzWymBpbofBrnU9FSeXvA0FcMr0r5me0zzBDfcsBaXy/cHZrVmnXRCUqNGKqtXp+PxSNxuD4axI+hb5bGxdxIVdR2GsY7IyNIMG5aA253G0qUbcDim5Nh7xjTNzBEaN2/cyLAhQ/B4vdjCwnhj4sRsIzN2yqfRCoNZ82rNmX/ffBx/Onh24bPEzInhdfN1xnUfR49rewQ6vBJNJfIg98+pf/jrxF883uZxmlZtSsKHu3G7z7WSvF5Jnz5Xc+ZMCn37VicqSvDTT7/hdnuw2azoev0ARp9/NK0xmtaYhIQPs8xilI5hrLpgIjdNE7u/dBISEkJIejrSNw4wbpeLw8nJzHY4WGYYdNL1EltWuRB7PTu/PfobX/z+BSN/GclNH99Et3rdeK3ba7Sq3urSB1DynUrkQa52hdp0q9eND9d+yMSeE9H1ithslswWeWhoKM8+WxdNK5O5j8MxpNjUyM+n69HYbKFZbnC6cFnRyFI68Xq9SCAU3+cWq8VCF3/yVgn8wizCQr+oftx5/Z28v+p9xiwZQ+vE1twbdS9jbxhL3YrF6/eqqFMXO4uBbzZ/Q98v+5LUJ4n+zftjmidISvoHsBITc1W2JF4SmOZ6DGMVuh590bJK1hZ5uJR409OxWK28MWkSD8fGFnLUwe1E6gnG/TqON5e/Sbo3nSFthjCyy0gql6oc6NCKBdWPvATwSi9tp7blwMkDbH18K2XDygY6pKCQtUZuAT5LSkIA/WJiaHuRlvhy02SpYdBZ12mvWuzZ7E/ZT5wRx7R10yhjK8PzHZ9naPuhlAotFejQgpqaWKKE+PWvXyVxyKmrpwY6lIByOlfI+PjXpdO54rL2W+F0ymoREbKS1SqrRUTIFTmMbmg6nbJiRIQsbbXKihER0gzSURAL2qZDm+Rtn94miUNe/frV8oPVH8h0T3qgwwpaqIklSob2NdtTLqwca/4uGpMwBIJprsRu782oUa9gt/fGNFfmet/cdjdcet52S0twt8SLaVylMd/1+44lDy6hZrmaPDL3EZq934x52+b5hl1V8pVK5MWERVhoe3VbPv/9c2Zvnl0i/1gMY1m2JGsYyy65z2rT5N2EBKpERmKz2fyzF+Xc3bCzrmfbrrPqlnhRnWt3xhxg8vXdX5PmSeO2z25Dn6Ff1qxXyqWpGnkxsvXIVvp80YctR7YQ0zyG17q9RrUy1QIdVqHJaJFn9P12OL696I1Aq02Te+32zJntX5w4kcPJyXTSdVUjLwBpnjQ+WPMBcYvjOHT6EHc1vov4G+NpENkg0KEVeepiZwmT7k1n9OLRxC+N9407Xa873et15+4md1OzXM1Ah1fgTHMlhrEMXe90ybs5301I4PVRo/B4PFitVp4eM4YhI0YUUqQl10nXSd4w32C8czwuj4vYVrG81PUlripzVaBDK7LynMiFEOHAEiAMX7/zr6WUL/vXPQE8DqQD30spn73YsVQiLzzbk7czZfUU5m6by7bkbZS1lWVKryn0i+oX6NCKjPNb5J86HLRWLexC88+pfxi9eDRTVk8hIjSCZzo8w1PaU5SxlazusrmRH4lcAKWllKeEEKHAMmAoEAGMBG6VUrqEEFWllIcudiyVyANjW/I2Hv72YX7d+ysPt3iYyb0mY7PaAh1WkbDaNFluGLTXdZXEA2Rb8jZecLzArM2zuKr0VcTpcQxoOYBQa2igQysy8jxolr/3yyn/y1DO3QA3GHhVSunyb3fRJK4ETsPIhhgPGjzf8XmmrZvG2yveDnRIRUZrTWPIiBFYgcSEBNaVsCFri4KGkQ35+j9fYw4waRjZkMHfD6bp5KbM2TKnRF60vxK5qpELIazAaqA+8K6U8jkhxDrgW6AnkAoMl1L+doF9Y4FYgFq1arXes2dP/kWvXLZbPrmFJXuWkHhbIn2u66Nu1ADWmSYPZxmydprDQQvVOg8IKSXzts3juYXPsfnIZrrW7srrPV7PcdKUkiJfhrGVUnqklC2AmkBbIURTfPXyikB74BngS5ExC3D2fROllNFSyugqVYJvMoPi5oPbP6BR5Ubc9819VHytIu/9pmbNWenvG+71eEhzu1mp+oYHjBCC2xrdxobBG5h862T+OPwH0VOj6T+7P3tP7A10eEXWZfUjl1IeBwx8rfB9wDf+0stKwAuogRWKuBpla7DikRUsuH8BXWt35cn5T7Jkz5JAhxVQbbP0DQ+12Wir+oYHXIglhEHRg9jx5A6e7/g8X236ioaTGjLSMZKTrpOBDq/Iyc3FzipAmpTyuBAiAlgAvIavdV5DSvmSEKIh4ABqyYscUF3sLFpSXCm0mdqGAycPMLLzSGJbx1IpolKgwwqIdabJSsOgra6rskoRtOf4Hl745QU+3fgpVUtXZbQ+mgGtBhBiKRkDuOZHr5VmwAzAiq8F/6WUcrQQwgZMA1oAbnw18l8udiyVyIue/Sn7eejbh/j5z5+pVqYab970Jv9t8l8uUCUrETaaJmsMg1a6TpRK6EXOyv0reXrB0yz7axlNqjRhfPfx9Kzfs9j/vqobgpRcWfP3Gh6c8yAbD20ksVcij7Z+NNAhFbqNpsnjdjtulwuL1crTkyZxpxrOtsiRUjJ7y2yeW/gcO47uoHu97kzoMYFmVzULdGgFRs3ZqeRKq+qtWDtwLdE1oolbHMeRM0fy7dimuZGEhBmY5sZ8O2ZBWGMYuF0upNdLeloarw4ZorojFkFCCO68/k42PbaJN296k1UHVtFySkse+e4R/j75d6DDCwiVyJVMVouViTdN5NDpQ9iT7Bw8dTDPxzTNjdjtjzNq1BTs9seLXDL/JPED+rTrwCN39KVUZCQWq5WMz6hpXi+rgqAHyzrTLJF94G1WG8PaD2PHkzsY2m4oSeuTaPBOA0YvHs1p9+lAh1e4LjbGbX4/1HjkwWHu1rnSNsYmrf+zyo4fdpSPf/+4nLt17hWNJx0f/5G0WjUJ7aTV2kHGx39UABFfmY+nTJXNQbYA2Rxk7RCbfOPZZ2WbkBDZwmKR0RERcm0RH298rdMpW0ZEyCZWq2wZBPEWpO3J22XfL/pK4pA1Xq8hp6+dLj1eT6DDyheo8ciVy9WrYS/WD1rPcx2fA2D6uunc9tlt3PfNfaR50i7rWLreCpst1D/sawi6XnQm5/1p1jcIyHyQ7iG0QgUSlyxhyNixTA2CG4NUH/hz6leqz9f/+ZqlDy2lZrmaPPTtQ7RObM0vuy7aB6N4uFiWz++HapEHpzPuM3LM4jGSOGTnaZ3l5sObL2t/p3ODjI//SDqdGwoowitzoRb5qiwt2nVOp/wgPl6uK8Kt3IwWeVPVIs/G4/XITzd8Kmu/WVsSh+z1aa/L/r0tSrhEi1z1WlFybeb6mTwx/wnOpJ3h+U7P80LnFwgPCQ90WHnySeIHfPXhNCrXqM7gZ4dnDpyVlDiTFx57mlKeU1QI8zJ10SK8wNdJSZxB8J+Y/mhFpLWu+sDnLDU9lbeWv0X8snhOu08zsPVA4vQ4qpQOrrvMVfdDJV8dOn2Ipxc8zccbPubqslfTrmY7mlZpSr+oflxX+bpAh5cvTHMtXTrfS7rHg0ByLfto36Ut61eswOVyIYFDtlLMNxYWmWSuXNzh04eJM+KYsnoKpW2lebHziwxtPzRoRgFV3Q+VfFW1dFVm3jGTn/v/TLua7fjj8B+MXjKaztM74/F6ctwvMXEBN930ComJCwox2itjGCvxeL2AQCI4RQRLli7ljMuVWU8PTXNhGCV7aINgUqV0Fd699V02Dt5Ip1qdeHbhszR9r2mxmUNUJXLlinSr141Z/5nF+kHrqVW+FhEhETneXZeYuICBA79kwYLdDBz4ZZFP5rreFpvNBkgEEhdnOYaVVEsIZ7CSjI2z1jB0vUugQ1Uu0/VVruf7e7/nh3t/wCIs3PbZbdz8yc1sPrw50KHliUrkSp58/cfX/HXiL9686U0s4sK/TrNm/QZZ+of4XhddmtaSRYuSuLtPZ8pb/uYYkpMyhH9EBAcsZTkqwkm3lsY3aoUSjG5ucDMbB2/kzZveZPm+5URNjmLYj8M4dvZYoEO7IiqRK3lSLqwcAEv/Wppj18S+fdvgm4vE9/C9Lto0rSVfzv6Qe2MfQvj/QXm8Eq+USAnp6ekYxtIAR6nkRag1lGHth7H9ie080uoR3l7xNg0nNWTKqikXLRMWRSqRK3lya4NbeSz6Md5a8RbN32/OV5u+It2bnm2b2NgeTJnyH9q2rUKfPtcSFRU8k0DfH3Mf4eHhviFuQ0Myh7u12WzoeudAh6fkgyqlq/B+r/dZM3ANTao0YdD3g2iV2ApjtxHo0HJN9VpR8sW3W75lhGMEm49splJEJXo17EWTKk0oF1aO6BrRpO0phd0+Arc7DZstFIcjAU1rHOiwc8U0l2MYS/2J25L5XNPaBjo0JZ9JKZm1eRbDFwxnz4k93NX4LsZ3H0+dCnUCGpfqfqgUGo/Xw9xtc/n6j6/5ccePJJ9NBnxjYrxkmc7LL32Mx+PFarUwZkwMI0bcE+CIFeXCzqad5XXzdRKWJeCVXoZrw3m+0/OUtpUOSDyq+6FSaKwWK32u68PHd37M4WcOc2rEKRpFNqJCeAVuvKGF/1Z9CzZbKLruG3LUNLeTkDAX09we4OgV5ZyI0Ahe7PIiWx/fyp3X38nYpWNpNKkRv/71a6BDu6CSMb2GUuiEEJS2leaa8tewNXkr/9v5FA7HGxjGBnS9GZrWGNPcjt3+Gm53OjZbCA7Hc2hag0CHriiZaparySd3fsJj0Y/RaXonJv02iY61OgY6rH9RiVwpULP+M4vyr5Znz4k9aFrjbHXxpKRFpKYeQ8pQ3O5wDGOLSuRKkdSxVkdql6+NoGjORKRKK0qBKhdWjmsrXsuWI1sYvmA4rnQXAKb5B9Onf4uUJ4GjWK0edL143OKvFE9n0s6w8dBGth7ZGuhQ/kUlcqXA/XT/T4RaQnndfJ31/6wHwDDWk57u66srhODhh9up1rhSpCXYE/jrxF9ET43mwMkDgQ4nG5XIlQJ3baVraRjZkOsqX0ebGr6bgXS9OTZbKBZLKazWqrRs2STAUSrKxQ1oNQDnw07SPGncOOPGIjVOi0rkSqE45T7FSdfJzLlANa0xEyc+hdVaD6+3MsOG/YBp7gpwlMHFNDeRkPApprkp0KGUGE2qNuGH+37AK73c9tlt3Jh0I/tT9gc6LJXIlcIxpM0Q9p/cz7xt8zKXJSen4/VKvF6J2+3BMHZk28c0d5CQ8D2mueP8w5V4prkJu304o0ZNw24frpJ5Ibqx7o1semwTk26ehHOvk0HfDwp0SKrXilLw3B43s7fMJjIikrsa35W5XNfrY7OF4HZ7sNms6Hr9zHWmuQO7fXyWronPoGn1L3T4Yss0t2EYf6DrjdG0htnWGcZ63O40PB4vbncahrEeTVPlqcISag1lSNshnEk7w7MLn+W7rd9xe6PbAxaPSuRKgft558+Y+0zG3DCGsmFlM5drWl0cjscwjB3oen00rW7mOsPYitudjseT0VrfWqISuWluw24fm+Uf2YvZknnGNYaMIQ90vXmujrvGNJmVlMT+gwepWK0a98TE0E5NjnHFhrQdQvyyeHp/3pvdQ3dTu0LtgMShErlS4CpGVEQgGLNkDNPXTSeqahQ317+ZmOYxaFrdbAk8g643Oq+13igAkec/01yPYaxC16PRtJyTr2H84f9H5sXtTscw/siWyDWtCQ7HBAxjPbrePMfW+HLTZIlh0EXXsQH333ADLpevC+gx4OPp05m3aJFK5leoVGgpvrvnO2799Fbun30/Sx8KzIiYKpErBa7DNR0wB5gkrU8i+WwyK/ev5Nut3zJn6xzm9ptLiOXcr6HH6yH5bDL1osoyc+49mCt20r5dPVpEXx3AM/Axzc1Z7ky9/jL3XUtS0ndMnz6P9PR0/8BhU3NM5rre2P+PzNci1/V/DzCmaU0umMBNcy2GsZLKkaV4dthA3G43NpuNwQ88gNvtRuAbUNgGnHW7WWYYKpHnQefanYltHcvr5uu8veJtHmn1CKVCSxVqDCqRK4WiXc12tKvZDvCNMDdq0SheWfoKt3xyC2EhYew+vptDpw9x5MwRvNKbfedlvkfp0NKEWEIoF1aOtle3pce1PWhVvRUtqrUgxBKCx+vBIiyZMxV5pRe3x80p9ykqRVTKceKL3DDNzf7RGzNKHQm5TubPPfc248cn+buqeYGMVvaqHBO5pjXE4Xgxxxp5znGuxW5/ELfbjcUisHgEeD243W72HDyOV+JP5IJUbNhs0EnXc3VsJWcNKvnugRj641ASliUwXBvOwOiBlLGVKZT3V4lcKXRCCOL0OPam7GXBzgVULlWZ+pXq0/GajlQtXZXKpSpjFVZK20pjERa80sv+lP0cPXuUdG86R84eYcmeJczaPAuAyqUqIxAcOXOEyqUq075me8rYyrDwz4UcPnMYgLK2svSs35NbG9zK3U3uvuwWk2FsOK/UsSFXiTwxcTbjxk3PssQGpPlb2TkOZgf4knluE/i5OFfidrvxeLxIacFqKYNFuLDZbJSr1oB/LNdi854kldK0atuYNya+oFrj+WBg9EAGRg9k6Z6ljPxlJMN/Hs6by9/k7sZ3M7jNYBpGXt7P8XKpRK4ERIglhBl9Zlzx/lJKdhzdwYr9K5i/Yz5lQstQtXRV9qbsZeX+lZxNP0vHWh2Jrh5NaVtp/jj8B3O3zeWrP77imZ+fYUibITza+lFqlK0BQGLiBmbN2kGVKhYOHz5KixZVqVDBhq43QNPqEhlZBotFIKXwJ+Fm/4rJNH/HMNah6y3QtKYAzJr1y/mR07ZtMyZO/L+L1sivVMZ8oxkXQd+aOIFjyfvooutISjFjxo+cdJfBZgtlwsSxtCuAGEqyzrU7s+ShJfz616/ELY5j8qrJJK5JZGH/hWjXFNw/TDUeuVJiSClZ+tdSXl32KvN3zMcqrPS+rjfX/NOdt546A+k2/5b/AMcRAsLDQ3niiba88cbneDwurFbBu+8OITb21mzHNs3fsdufyjJxxhtoWlMSE2czcODoLFuWokWLGN5773Y0rXqBnGdGjVzX26JpLc9btx7D+I2qkTaOJ++nk66rFnkB2p+yn64fdeV46nH++r+/rrh2riaWUJQL2Hl0J1NWT2Ha2mm+CTC8Fph3D6zRgOP4kjlYLAI4hdd72v86hbFj+6PrbTGMzURGRrB27XbWrNnKqlXr8HolFksY0dEdqVGjEVCFBQuWc+bMMeAU0AKoApzm2Wcb8tpr7bPFZZpHMIxD6HpVNK1yvp5zxieGqpHwwrDYzIug3zkcKpkXkB+2/8ADcx7gyJkjbB6ymesqX9nAcCqRK8pFpKan8tR77zN5ewJUPgTjX4HTZ4HjWCwCq1WQnn4UKdOAcCyWMIYP78Y77yzA5UrD6/UCKUC6/yGA6sA1/ucCuBoI9z+v5n+eDpymQYNSVKxYigEDriYqKgy7fRFutwerNZ2HH76amJhGaFoNTPMvDGMXul4XTav1r/MwzdUYxnJ0vT2a1vpf6xMTf+Kxx97D4zlLuGUnoXIXSInFYqVztx68EPcymtYu376vprkSw1iGrncqkVPiHT59mGd+foYZ62dQq3wt+jTqw8SeEzMvxF8ulcgV5SJS01OZtHISz/z8DACdDzxL2uFwOjeIpmKFMCIjwxg27ENSU0OQshZCWLBaT+D1JuP1Snwd+c4AqYAFIcKQ8iqgMmSOXV0JqOh/HomvRS7xXaIK9z8/TosWYaxbl4rvE8FuwEVoKGhaJEuX7kBKCAkRLFnySGYyN81NjBs3k7lzv0PKVMLCbDgcn2RL5s899y3jx3/l7zUjEeymNCvw9aABl6UMIWGlcDi+y5dkbporsdv7ZLb4HY45JSKZn3Kf4qtNX/HK0lf489ifSCQjO49kVJdRhIWE5enYl0rkl7zYKYQIB5YAYf7tv5ZSvpxl/XBgPFBFSnkkT9EqSiHxeD0krU/iZeNl9qbspXu97tQsV5MvQ9/ldI3TpFRpTL+m/ahSpQkfftePaeN388vCw3i94PWGYbVaAK8/maf7jyoAL1arC49HZlkWgS+Bl8fXa8UKlPOvz5gDsiLr1mV0u0wGTgOHSEs7wZIlf/r38ZKe7uX553/g1Ve7kJT0Ex984OuX7vvHcZqzZ0+RlPRtZiJ/7rnvGTfu+yyxgCSSM2iEsJ10TuL1StJTz2IYy/IlkRvGMn/PGV+3R99xi28in7RyEnO2zGHZX8tweVy0qt6KOD2Ovtf3pUnVwhk2ITe9VlzAjVLKU0KIUGCZEGK+lHK5EOIaoDvwV4FGqSj56KcdP/HUgqf44/AftL26LS90foFPNn7C9HXT6Vm/J7c3vJ2kDUmMWjQqc5/yXStCpaux/N6YsJ3NmThxAMnJR4mMjGD+/JXMnfsbUkJYmJWJE//L2rWHOHjQAlRh1aoy7NuXtUVWCqiArxWf9aO2BTgKrMTXWrb5H1k/NR9mw4at2O3fc/bsGcDDuRJOWaAsiYk/ExNzN1CGCRN+JvufuW87L+CmOnAS8CKll+PHz+RLSUTXO/l7zvha5Lre6YqOEwy2HNnCE/OfoGa5mgyKHsTtjW6na+2uWC3WQo3jkolc+j6PnfK/DPU/Mn6z3gSeBb4tkOgUJZ95vB5u++w20rxpdLymI9dVvo5hPw6jVGgpZvSZQf9m/RFCMLjNYA6fPszu47v54/Af/LTzJz5L+wyu+51J7frTs2NdapT1zd0YG9sN09yCYfyOrjelbbsGnHCd4KTrJNXLVufaOjvxtYcyWPG1xMvgK6NARmve1xrPekNUqH/fjPsx0zlx4jDnEnhW/huhvCEYxlqgGl6vB98/DDcQQYsW9alTJ4Q5cwx8JZ/6wH7gLIbh5J13Jue6JGKav2EYv6LrHdG0NpnLNa0tDsecYl8jT/emM23tNADev/V9bm146yX2KDi56kcuhLACq/H91N+VUq4QQtwO7JdSrr9YAV8IEQvEAtSq9e+LNIpSmCzCwuNtH2fK6in8uvdXNh3exF2N72JCjwlUK1Mt27ZVSlehSukqtLm6DQ+0eID2Ndsz9MehDFhxG6yAm+vfzP3N7ic1PZUvdn7Bb5bfGP3LWVIXpGYeo1b5WkS2eI19+7L2ViiLr1IJvtq5G1+S9gBXAVs511aycS6J+9pUUnoRIgRI49yfcEZiPw2cJDLShq/ksxHfPwtfG6x9+7acPHkK3z+RjPcvC2ylRo0qrF6du5KIaf6G3X5nlu6W3/wrmRfXBA7w6cZPuf+b+5FI+jXtR8/6PQMaT64SuZTSA7QQQlQAZgshmgEjgR652DcRSATfxc4rD1VR8k4IwRs3vcFr3V7jpPskFcMr5ronwRNtn6DDNR3Yn7KfDf9sYOKKiczfMR/wzbZ+T9N7KGMrQ0RIBBUjKhJqCWXiiolsbTsAsekt5K72+MonHnxJWXDuQ+4x/+sqZG9pp+BL7GH4WuZnAEn9+mXZteskHo9ECBterwBOALsRAp58cjgeT3nO/UNIw1fSSWXFiu0Z3w3/+lL06XMfzz57Hz/9tDBXJRHD+NU/jK4Ht9v3OmsiL+4mLp+IRPLOze/wWJvH8jT8Q364rDs7pZTHhRAG0BuoC2S0xmsCa4QQbaWUB/M9SkXJZ6HWUCpFVLqsfYQQRNeIJrpGNL2v683znZ5ny5EthIeEc22lay/4x3xX47vo+lFXtj7wKOXnTObEurbAn/gSdxV8vVbS/I8UwAkcwfenuR3fB+GMJCz826eyfXsazz4bQ4UKZdH11oAgLm48Cxfuwev14na7kdKN75+E7x+D1QoxMT0oV64C48b9gC+Jn0aIo9x8s68EMnHiGGbNmk3fvndctEWt6x39w+iCzRZKZGQkCQmT0HXtgt0fi5sn2z1J/9n9qVamWsCTOOSu10oVIM2fxCOAbsBrUsqqWbbZDUSrXitKSRJqDSXqqqiLbnNVmauoU6EOW5O3UrPNBk6sE8AhfH0EkvG1zqvg69Wy17/OBWwD1uOrX6fjK4HU4lx3RS8TJnzOsmXvo2m+GOLiHmfp0l9wu9MICQnB47GRng5wFiFcPP30/WhaVOb206fPIzl5NwDDho0BUhk2bBhut5ulSxcTFdUYsGAYS9H1ztl6tGhaGxyObzCMX4mMjGTYsDFZyiyfoWmtMc01GMYKdL0dmtYqr9/uImXRrkUAdKpVNC7k5qZFXh2Y4a+TW4AvpZTzLrGPoih+S/Ys4c7r7+Tp7iPoOPV9fCUQB+f6lgugOb569mlgD+cueJ7xfz0EXI+vm6EE9uD1nmHcuM+YPduXmLMmV13vCIQybty7zJ37CVJ6eeedV+nT5wY0rT2vvTaAChXSGDVqc+YsQ7Nm/ZCt22BS0sfMmPFVloufc/+VzDWtDQkJk84rs5iAwG7vn2XfmcUqmWcMgpV8Jvlf11YC4ZKfCaSUG6SULaWUzaSUTaWUoy+wTR3VGleUC2tVvRULdi7gR9dUHn0u44J/xgVO8LXK1wPHwLqHc/VzT5ajSOCwf7nvLlMI4bvvVpGY+A0JCW+QmPghhrHQ3wJug6a1oG3b+oD0lVtcLsbE/Y8VpgmArrfDZrNhtVqx2ULp2/eWLK9tgOW8/uAXnjRB1zVsttDM4+i6RlLSHFJTM2Z4SiMpaTYJCZMxzTX5+a0NmAdaPADAF5u+CHAkPmr0Q0UpYF/c9QWPzH2EsUvGIiMk9eObcXjxVZz4pyqEpULUKqh0GMLP+nZY2hQWNwdvTXz19AyR+LoSHsWX2Mvg9bp57LHRSLkLr/ckFouFsLAwHI6FaJqGrnf19el2ufB4vSxe+DO9li5mnsOBpmm8N/EZ5sz6gT59b+HB2P5ERdXHMBaj610BCzNmfJHl4mfnC56fprXG4fgMwzDRdQ2wMn36XKQMAaxYLJJp077G4/H4W+dJQd86//qPrwEozDvjL0YlckUpYFeXu5r5981nX8o+Pt7wMR+t+4gT2s/nNjhSDr3y7ZBalwPuJWzr+isR2j56Vb6LWS+Uw5ua4t/wD6Aevj/bjB4nKXg8RzjXh9zrbz0baJqGprXH4fiJMXH/Y/HCnxH+SSaWGgY24PVhA3G7XGxdNItQznJfbCxalgG0HI65F6yRn0/TWmde5ExImOq/2xSEsNCyZWNWr16XZaLoFUGfyOdumwvAi11eDHAkPiqRK0ohqVmuJs93ep7nOj7HP6f/wblyAyuXb+P2fjodOvjGL5dS8v327xnvHM9Xe6ZS9sWyhG+J5PCPJ+CIG/gLi6V+lnFeDuK7OxPAhsWSTkhICH/9tRfTXI6mtUfT2vNy3Ev0Wro4s3XdWddZYRi4XS68Xi8er5cRQ4bQICqKtlkSuaa1u+zb9nW9TbYx0QcM6MvGjX9kmSg6/wbnCoSTrpMs2LmAa8pdk+cxVPKNlLLQHq1bt5aKouTO8r3L5X+++o8MHR0qiUOGD64gbx1xj1y0dK0cNOhNKUQjCeWyPCrL669vLW220tJqDZcREeWk02meO57TKcfHx8vlTqeUUso1Tqe8LjRUXgvyWpCVQQ4bNChfYnc618r4+ETpdK71v14t4+Pfk07n6nw5fqCcTTsrn/zhSUkc8r9f/bfQ3hdYJS+SW1UiV5Qi7p9T/8hxy8bJ+m/Xl8Qhq02oJj9c86F85tkx5yXyarJt2+7Sag2XECqt1nAZH//qRY/98ZQpsqbVKiNBlgNZyWbLTPRKdvtO7JP13qoniUM+OOdBefTM0UJ770sl8sD3ZFcU5aKqlq7KMx2fYevjW/m5/8/Ur1SfAd8NYF/bPxj43CMgwoBShIVFMGDAfdl6nuh6V0xzBQkJEzDNFf869n2xsfR99FHShMADpHs8LDWMwj7FIm3ToU0s2rWIe2bdw6HTh/jxvh+Zdvs0KkZUvPTOhUTVyBUlSFiEhW71unFj3RtJWJrAS8ZLeCO81BlXlw6uGxlywyA6dIgmKqpRlp4nAru9V5b+3PP+VfPuFxPDJzNmZKufKz5SSlontsblcWEVVqbeNpWb6t8U6LD+RSVyRQkyFmFhZJeR9L6uNwv/XMiU1VP49PSHbFy/kqdLPc29be9F03xTyCUkTLhAX3CJYSwhMrISycnJ6HpX5jkcLDUMOqs5PLM5lnoMl8dFxfCK/P7Y75mTdRc1KpErSpBqWrUpTas25Ym2T/DJxk8Y7xzPg98+yOglo5neezpdandB1ztjs9lwuQRClOb48TPY7T1JTU1FSumfYDoch+Mnho8YEehTKnI+2fAJ4EvoaZ60AEeTM1UjV5QgZ7VYiWkew4ZBG5jbby5WYeWGGTfw8qKXadOuNRMnvoXVWhOvtzxvvPEhqamuzGnfpJS4XG4MY3GgT6NIeqzNYwzXhgPwwZoPAhxNzlQiV5RiQghBr4a9WDNwDf2b9Wf0ktHoH+nsOvI3Xq/0PyKyDNsrgKpAOf9F0XUkJEzFNNcF7iSKGKvFSt/GfYFz46sURaq0oijFTBlbGT7q8xE9ru1B7NxYkiOOEVoqHM4IbLZyPPHEi0yYMBmvtxpQHq8X5sxZxTvvTM9yUfRDNK1FoE+lSPhh+w8ANLuqWYAjyZlK5IpSTN0bdS9lbWXp/Xlvuo/viX60L7oezcaNBylTRiMlJYWMSS6++caBy+XF6w3D5fJiGL+pRO735vI3Adh9fDcVIyqS4kqhRtkalz2efUFSpRVFKcZua3Qbo7qMYsHB+XR/oDkbNx5k4MD3SUlx4xtB0TdJcLt2LfB6ywGl8XrLEhlZOZBhFykz75hJeEg4fb7oQ+2JtYmaHEXkuEi6z+zOKfepSx+gEKgWuaIUc093eJqJKybyuvk6R2c14twwuZJKlSryyCM3s27dTjIG3hICkpPPXOSIJUuf6/pw+JnDfL/tew6eOkj1stXZdGgTY5aMocX7LVj60FKql60e0BhVIleUYq5cWDliW8Xy5vI3GdN7GgsWrCcjmT/yyK28884Kzp49gG8yC4GUkuPHkwMbdBFTxlaG/zb977kFTXxfRi8ZTdL6JJ7r9FxgAvNTpRVFKQEebPEgHumhbHQKU6YMokePFjz77D2sW3cWlwvgFL6JK04Ah1m3bn1A4w0GGYn9z2N/XmLLgqda5IpSAmz4ZwMAba9uS9u2bYmKuh5d/xy3uyy+KeSqAbuAzcBJUlM9mOa6In3Bc6Vp8mVSEqHAXTExtPbfkWqayzOHKMi4w7UguNJdADSv1rzA3iO3VCJXlBLAK31zgEaERACQlLQVt7sWvl4rKUApfPWC64GlLFmyj86dB/Pee88RG9snIDFfzErTpLeuY3O7AZg1fTqfLVqEG4HdflOWbpQ/FUgyf2fFOwz/eThlbGXo1bBXvh//cqnSiqKUAC2rtwRg7cG1/iVlODcvaNa5QQXQCKiJx3Mtjz32Lqa5+ZLHN83VJCS8i2muzte4c7LUMJBpvlvmBZDmdrPcMDCMxeeNLZP3O1ZPpJ7gwMkD7EvZx86jO/l046cM/XEoNcrWYMuQLdQqX+vSBylgqkWuKCVAo8hGlAotxaoDq4hpHkNMTAOmTt2Lx2PF1wUxYxwRiW9e0DDAjcdTCsPYgKZdn+OxTXM1dvu9mTMAORyfZk77VlA66zoTQkPB7UYCFouVMpFX0yqqoX92InfmML7p3nROuU9x0nWSk+6Tl/7qPpm5/d+n/s4sS2VVKaISb/R4g6vLXV2g55lbKpErSglgtVjpWrsrX//xNSM6jUDTqtO6tY2VK91ABL4P58fwTR2XBoT6HxAZWf6ixzaM5bjdaf5WsO91XhK5lJLTaac5kXrigon2lPsUJ70nueWD+3AuX8qu/ftIt4Xw8LIniTpbj5pjryL5ZDLeUMmNv9xA6oLUXL2vRVgoaytL2bCymV+rlq7K8x2fp06FOlgtVizCQtOqTWldvTVWi/WKzzG/qUSuKCXEyM4j6T6zO43fa4y9rp3o+7qycmUp/1orvoSehq81DlARIVJJTr74TS+63h6bLRS3G0LDQmjV8Xp2HdvFCdcJUlwpnEg9wQnXCU6k+l9nPHdfeF2KKyWzpn8ptqphuCO84JLg9pJy4gxNG1xH2Tr+ZHxeYs74WsZW5l/LIkKyjkMTXIRvFLTCER0dLVetWlVo76coSnZbjmzhf4v/x+e/f+4bAtf6GbNm/UlUi/K8O3UDqd5dYEsGWxqEubCUOsbzL9upUrN0ZtLNmowzXh85eYQTrhTScF8yhlBLKOXDy1MurBzlw8pTPrw85cOyvy4XVi7zcaFkXMZWhtK20qxYvhG7fSBudzo2WwgOxxQ0LfC9SPKbEGK1lDI6x/UqkStKyTP+1/E8u/BZyoWV42zaWdK8uRtru3Ro6X8l4czn57/OIVmHh4Tna8vXNNdjGKvQ9ehimcTh0olclVYUpQQaFD2II2eOcCbtDGVsZbI9Duw5y44/jtOuRQM6tr4uWws5xFL0UoamNS+2CTy3VItcURSliLtUi1z1I1cURQlyKpEriqIEOZXIFUVRgpxK5IqiKEFOJXJFUZQgpxK5oihKkFOJXFEUJcipRK4oihLkCvWGICHEYWBPob3hOZWBIwF438JWUs4T1LkWRyXlPOHyz7W2lLJKTisLNZEHihBi1cXuiiouSsp5gjrX4qiknCfk/7mq0oqiKEqQU4lcURQlyJWURJ4Y6AAKSUk5T1DnWhyVlPOEfD7XElEjVxRFKc5KSotcURSl2FKJXFEUJcgVq0QuhLhbCLFJCOEVQkRnWd5dCLFaCLHR//XGC+z7nRDi98KN+Mpd7rkKIUoJIb4XQmzx7/dq4KLPvSv5mQohWvuX7xBCvC2CZEbdi5xrpBBikRDilBBi0nn79POf6wYhxI9CiMqFH/nlu8JztQkhEoUQ2/y/x30LP/LLcyXnmWWbXOekYpXIgd+BO4El5y0/AtwmpYwCHgBmZl0phLgTuPhU4UXPlZzrBCnldUBLoKMQ4uZCiTRvruQ8JwOxQAP/o2chxJkfcjrXVGAUMDzrQiFECPAWcIOUshmwAXi8EOLMD5d1rn4jgUNSyoZAY2BxgUaYP67kPC87JxW9CfjyQEq5GfjXxK5SyrVZXm4CwoUQYVJKlxCiDPAUvj/8Lwsr1ry6gnM9Ayzyb+MWQqwBahZSuFfscs8TqASUk1Ka/v2SgD7A/MKINy8ucq6ngWVCiPrn7SL8j9JCiGSgHLCjEELNsys4V4CHgev823kJgrtAr+Q8ryQnFbcWeW70BdZKKV3+12OA14EzgQupwJx/rgAIISoAtwGOQARVALKe59XAvizr9vmXFTtSyjRgMLAROICvlfphQIMqIP7fWYAxQog1QoivhBBXBTKmAnTZOSnoWuRCiIVAtQusGiml/PYS+zYBXgN6+F+3AOpLKf9PCFEnn0PNs/w81yzLQ4DPgLellH/mV6x5kc/neaF6eJHpY5uXc73AsULxJfKWwJ/AO8AIYGxe48wP+Xmu+HJVTeBXKeVTQoingAlA/zyGmWf5/DNtwRXkpKBL5FLKbleynxCiJjAbiJFS7vQv1oDWQojd+L4XVYUQhpRSz49Y8yqfzzVDIrBdSjkxj+Hlm3w+z31kLxnVxNdaLRKu9Fxz0MJ/zJ0AQogvgefz8fh5ks/nmoyvhTrb//orYEA+Hv+K5fN5XlFOKhGlFf/Hsu+BEVLKXzOWSyknSylrSCnrAJ2AbUUliV+pnM7Vv24sUB4YVviR5a+L/Ez/Bk4KIdr7e6vEAJfb+gsW+4HGQoiMUfG6A5sDGE+Bkb47F+cCun+RHfgjYAEVkCvOSVLKYvMA7sDXInMB/wA/+Ze/CJwG1mV5VD1v3zrA74E+h4I6V3wtU4nvDz1j+SOBPo+C+JkC0fh6C+wEJuG/g7moP3I6V/+63cBRfD0Z9gGN/csH+X+mG/AlushAn0cBnmttfL0/NuC7vlMr0OdREOeZZX2uc5K6RV9RFCXIlYjSiqIoSnGmErmiKEqQU4lcURQlyKlEriiKEuRUIlcURQlyKpEriqIEOZXIFUVRgtz/A6G6PH1b1+mEAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# all done with redo's.  Let's look at some outputs.  First, red/blue by home district  SHOULD BE MIX OF RED AND BLUE\n",
    "nPlot = 5\n",
    "for t in range(nTracts):\n",
    "    if(t % nPlot == 0 and tractPop[t] > minTractPop):\n",
    "        redd = min(max( 0, ( HDvGOP[t] - 0.5) * 3.0 ),1)\n",
    "        bluu = min(max( 0, (0.5 - HDvGOP[t]) * 3.0 ),1)\n",
    "        plt.scatter(tractCPx[t],tractCPy[t],marker='.',color=(redd, 0,bluu ) )\n",
    "x,y = MAP.exterior.xy\n",
    "plt.plot(x,y,color='green')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "a5d3b510-6d1e-49ae-9a5d-03352e2b449e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "map of tracts that were used less than 0.7 of expectation in CA\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Now, where are those UNDERPERFORMING tracts (<0.x usage)\n",
    "maxPlot = 0.70\n",
    "print(\"map of tracts that were used less than {0} of expectation in {1}\".format(maxPlot, STATE) )\n",
    "for t in range(nTracts):\n",
    "    if(tractUse[t] < maxPlot and tractUse[t] > 0.05):  #ignore skipped tracts\n",
    "        redd = min(max( 0, ( HDvGOP[t] - 0.5) * 3.0 ),1)\n",
    "        bluu = min(max( 0, (0.5 - HDvGOP[t]) * 3.0 ),1)\n",
    "        plt.scatter(tractCPx[t],tractCPy[t],marker='.',color=(redd, 0,bluu ) )\n",
    "\n",
    "x,y = MAP.exterior.xy   #turn these on if I pull map back in\n",
    "plt.plot(x,y,c=\"green\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "876011e8-d37e-44a6-8dd9-a1e4d2f51e58",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here is a map of tracts that were used more than 1.2 of expectation\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ... And where are the OVERUSED tracts?\n",
    "minPlot = 1.2\n",
    "print(\"here is a map of tracts that were used more than {0} of expectation\".format(minPlot) )\n",
    "for t in range(nTracts):\n",
    "    if(tractUse[t] >minPlot and tractUse[t] > 0.05):  #ignore skipped tracts\n",
    "        redd = min(max( 0, ( HDvGOP[t] - 0.5) * 3.0 ),1)\n",
    "        bluu = min(max( 0, (0.5 - HDvGOP[t]) * 3.0 ),1)\n",
    "        plt.scatter(tractCPx[t],tractCPy[t],marker='.',color=(redd, 0,bluu ) )\n",
    "\n",
    "x,y = MAP.exterior.xy\n",
    "plt.plot(x,y,c=\"green\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "19bfa7c8-0449-4182-8ed9-f5a1c1276f03",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here is a map of 90 tracts that were used more than 1.5 of expectation\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ... And where are the REALLY OVERUSED tracts?\n",
    "minPlot = 1.5\n",
    "counter = 0\n",
    "for t in range(nTracts):\n",
    "    if(tractUse[t] >minPlot and tractUse[t] > 0.05):  #ignore skipped tracts\n",
    "        redd = min(max( 0, ( HDvGOP[t] - 0.5) * 3.0 ),1)\n",
    "        bluu = min(max( 0, (0.5 - HDvGOP[t]) * 3.0 ),1)\n",
    "        plt.scatter(tractCPx[t],tractCPy[t],marker='.',color=(redd, 0,bluu ) )\n",
    "        counter +=1\n",
    "\n",
    "print(\"here is a map of {0} tracts that were used more than {1} of expectation\".format(counter, minPlot) )\n",
    "x,y = MAP.exterior.xy  #wholemap\n",
    "plt.plot(x,y,c=\"green\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "f3e9bde3-06f6-402d-bce1-62b5631e8db0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ERLRHsxrBU5IuBaZJOq/3Tttn1RdWRES0ykAPlL0aOJainyAiIkahZrePPgR8TdJdtpe1MKaIiGihKlNVriuHoZ7VeLztd9QVVEREtE6VRPBt4Cbg+8C2esOJiIhWq5II9rD914MtWNIlFP0MD9o+pI/9orgz6QRgM/B220sGe52IiNg1VRLBtZJOsL1wkGV/GTgf+Eo/+48HDiqXI4Evlq8jXs/9D/OtJWt58NEnEbBm42bu37iZJ7ZsG1ZzfI4RPGfsGMaNG8O0Sbtz+Mx9WLNxM8t/von5L5jKfQ89zrK1m56OeQywx25j2W/S7rzj6AN585Ez2hl+RAwR2c2/msrB5/YEngSeYhCDzkmaBVzbT43gAmCR7SvL9buB+bYfaFZmV1eXu7u7B7p02/Tc/zBv+tJitmzd3u5QavfxN7w0ySBihJDUY7urr30DTlVpe6LtMbZ3t71XuT4UI48eAKxpWF9bbnsWSadJ6pbUvX79+iG4dH0Wr97AUx2QBACuW9k0Z0fECDFg05CkY/rabvvGXby2+tjWZ/XE9oXAhVDUCHbxurWaN3sy48eN6YgawfGH7N/uECJiCFTpI/i/De8nAHMpHjA7dhevvRaY3rA+DVi3i2W23ZyZ+3Dln81LH0FEjBhVJq9/XeO6pOnAPw7Bta8BzpT0NYpO4k0D9Q+MFHNm7sOcmfu0O4yIiEqq1Ah6Wws8q/O3N0lXAvOBKZLWAh8CxgPYXgAspLh19B6K20dP3YlYIiJiF1XpI/gcPKN14DBgwCEnbL9pgP0Gzhg4xIiIqFOVGkHjvZpbgStt/7imeCIiosWq9BFc1opAIiKiPQZ8jiAiIka3JIKIiA7XbyKQ9C/l69mtCyciIlqtWY1gjqSZwDsk7SNp38alVQFGRES9mnUWLwC+C8ymeJK4cUgIl9sjImKE67dGYPs82y8GLrE92/aBDUuSQETEKFHl9tF3SXoZ8FvlphttL683rIiIaJUB7xqSdBZwOfAb5XK5pHfXHVhERLRGlSeL3wkcaftxAEmfAG4FPldnYBER0RpVniMQz5y0fht9zyUQEREjUJUawaXAbZKuKtf/ALi4togiIqKlqnQWf0bSIuCVFDWBU23/pO7AIiKiNSrNR2B7CbCk5lgiIqINMtZQRESHSyKIiOhwTROBpLGSvt+qYCIiovWaJgLb24DNkvZuUTwREdFiVTqLfwWskHQ98PiOjbbPqi2qiIhomSqJ4DvlEhERo1ClOYsl7Q7MsH13C2KKiIgWqjLo3OuApRRzEyDpMEnX1BxXRES0SJXbRz8MzAV+CWB7KXBgbRFFRERLVUkEW21v6rXNVQqXdJykuyXdI+mcPvbPl7RJ0tJy+WCVciMiYuhU6SxeKenNwFhJBwFnAbcMdJKkscDngdcAa4E7JF1j+85eh95k+7WDjDsiIoZIlRrBu4GDgSeBK4FHgPdUOG8ucI/t1ba3AF8Dfn8n44yIiJpUuWtoM/A35YQ0tv1oxbIPANY0rK8FjuzjuKMkLQPWAe+zvar3AZJOA04DmDFjRsXLR0REFVXuGjpC0gpgOcWDZcskzalQdl+T1/TuW1gCzLT9MooZz67uqyDbF9rust01derUCpeOiIiqqjQNXQz8he1ZtmcBZ1BMVjOQtcD0hvVpFL/6n2b7EduPle8XAuMlTakSeEREDI0qieBR2zftWLF9M1CleegO4CBJB0raDTgFeMbzB5L2k6Ty/dwyng1Vg4+IiF3Xbx+BpMPLt7dLuoCio9jAycCigQq2vVXSmcD3gLHAJbZXSTq93L8AOAl4l6StwBPAKbYr3ZoaERFDQ/1970q6ocl5tn1sPSE119XV5e7u7nZcOiJixJLUY7urr3391ghs/059IUVExHAx4O2jkiYBbwNmNR6fYagjIkaHKk8WLwQWAyuA7fWGExERrVYlEUyw/d7aI4mIiLaocvvov0j6M0n7S9p3x1J7ZBER0RJVagRbgE8Cf8Ovnww2MLuuoCIionWqJIL3Ar9p+6G6g4mIiNar0jS0CthcdyAREdEeVWoE24Cl5QNmT+7YmNtHIyJGhyqJ4Gr6GRU0IiJGvirzEVzWikAiIqI9qjxZfC99zFFsO3cNRUSMAlWahhoHKZoA/BGQ5wgiIkaJAe8asr2hYfm57X8G2jLyaEREDL0qTUOHN6yOoaghTKwtooiIaKkqTUOfbni/FbgP+ONaoomIiJarctdQ5iWIiBjFqjQNPQf4Q549H8FH6wsrIiJapUrT0LeBTUAPDU8WR0TE6FAlEUyzfVztkURERFtUGXTuFkkvrT2SiIhoiyo1glcCby+fMH4SEGDbh9YaWUREtESVRHB87VFERETbVLl99P5WBBIREe1RpY9gp0k6TtLdku6RdE4f+yXpvHL/8l5PMUdERAtUaRraKZLGAp8HXgOsBe6QdI3tOxsOOx44qFyOBL5Yvg65Wed85+n39517Yh2X6NfbLr6NG386PGf6HCvYe/fxPPHUNmZN3pO3HjWLles2IeDg5+/NynWbWPqzh9n4+BbmzZ7MQc+byLzZk5kzc592hx7RUXruf5jFqzfU8v9P9rNGmB6agqWjgA/b/r1y/f0Atv+h4ZgLgEW2ryzX7wbm236gv3K7urrc3d09qFgak8AOrUoGwzkJ7KwJ48dw+TvnJRlEtEjP/Q/zJxctZsvW7ew2buf+/0nqsd3V1746m4YOANY0rK8ttw32GCSdJqlbUvf69euHPNA63X7fxnaHMOSe2rqdxas3tDuMiI6xePUGtmzdznbX8/+vzkSgPrb1rn5UOQbbF9rust01derUIQmuVebOGn1TN4wfN4Z5sye3O4yIjjFv9mR2GzeGsarn/19tfQQUv+6nN6xPA9btxDG77L5zT2xbH8FX/vTIYd08lD6CiOFvzsx9uPyd80ZkH8E44L+AVwE/B+4A3mx7VcMxJwJnAidQdBKfZ3tus3J3po8gIqLTNesjqK1GYHurpDOB7wFjgUtsr5J0erl/AbCQIgncA2wGTq0rnoiI6FudTUPYXkjxZd+4bUHDewNn1BlDREQ0V+sDZRERMfwlEUREdLgkgoiIDpdEEBHR4Wq7fbQuktYDOzsi6hRgeN7Q37+RFnPirVfirddIixeqxzzTdp9P5I64RLArJHX3dx/tcDXSYk689Uq89Rpp8cLQxJymoYiIDpdEEBHR4TotEVzY7gB2wkiLOfHWK/HWa6TFC0MQc0f1EURExLN1Wo0gIiJ6SSKIiOhwHZMIJB0n6W5J90g6p93xDETSJZIelLSy3bEMRNJ0STdIukvSKklntzumZiRNkHS7pGVlvB9pd0xVSBor6SeSrm13LFVIuk/SCklLJQ37seMlTZL0DUn/Wf5bPqrdMfVH0gvLz3XH8oik9+x0eZ3QRyBpLMXcCK+hmAznDuBNtu9sa2BNSDoGeAz4iu1D2h1PM5L2B/a3vUTSRKAH+IPh+vlKErCn7cckjQduBs62vbjNoTUl6b1AF7CX7de2O56BSLoP6LI9Ih7QknQZcJPtiyTtBuxh+5dtDmtA5ffbz4Ejbe/Uw7adUiOYC9xje7XtLcDXgN9vc0xN2b4RGBETHtt+wPaS8v2jwF30Mff0cOHCY+Xq+HIZ1r+IJE0DTgQuancso5GkvYBjgIsBbG8ZCUmg9Crgv3c2CUDnJIIDgDUN62sZxl9UI5mkWcDLgdvaHEpTZTPLUuBB4Hrbwzpe4J+BvwK2tzmOwTDwH5J6JJ3W7mAGMBtYD1xaNr9dJGnPdgdV0SnAlbtSQKckAvWxbVj/AhyJJD0X+CbwHtuPtDueZmxvs30YxTzZcyUN2+Y3Sa8FHrTd0+5YBulo24cDxwNnlM2dw9U44HDgi7ZfDjwOjIS+xN2A1wNf35VyOiURrAWmN6xPA9a1KZZRqWxr/yZwue1vtTueqsrq/yLguPZG0tTRwOvLNvevAcdK+mp7QxqY7XXl64PAVRRNtMPVWmBtQ83wGxSJYbg7Hlhi+xe7UkinJII7gIMkHVhm0FOAa9oc06hRdr5eDNxl+zPtjmcgkqZKmlS+3x14NfCfbQ2qCdvvtz3N9iyKf7s/tP2WNofVlKQ9yxsHKJtYfhcYtnfA2f4fYI2kF5abXgUMy5sdenkTu9gsBDXPWTxc2N4q6Uzge8BY4BLbq9ocVlOSrgTmA1MkrQU+ZPvi9kbVr6OBtwIrynZ3gA+Uc1YPR/sDl5V3W4wB/s32iLglcwR5HnBV8RuBccAVtr/b3pAG9G7g8vLH4mrg1DbH05SkPSjuhPzzXS6rE24fjYiI/nVK01BERPQjiSAiosMlEUREdLgkgoiIDpdEEBHR4ZIIohblSI5/MYTlzZf0iqEqbzSTdJikEwZ7nKTXj4SReWPoJRFEXSYBfSaC8v79wZoPJBFUcxgwYCLofZzta2yfW1NMMYwlEURdzgX+VzlW+ifLX/Q3SLoCWAEg6epyQLJVjYOSlXNHLCnnC/hBOZDd6cD/Kcv7rcYLSfqwpPc1rK+UNKt8uvU7ZTkrJZ1c7p8j6Ufltb9XDqPdWN7e5Vj6Y8r1PSStkTRe0lmS7pS0XNLXBvoQJL1FxdwHSyVdUA52d0R5/oQyxlWSDik/oxslXVVeY0FDDL8r6dbyc/l6Oa4TZVm3lH/j7ZL2Bj4KnFxe82RJc8tjflK+vrB8aKr3cW+XdH5Z7szys19evs4ot39Z0nllOaslnTSofxUxPNnOkmXIF2AWsLJhfT7FQF4HNmzbt3zdnWL4gcnAVIqRYg/sdcyHgff1c61n7CvLmgX8IfClhu17Uww5fQswtdx2MsWT5r3L/DbwOw3HXFS+Xwc8p3w/aYDP4MXAvwPjy/UvAG8r3/898Cng88D7Gz6jX1GMhDkWuB44CZgC3EgxhwLAXwMfBHY8AXtEuX0viqd43w6c3xDHXsC48v2rgW+W73sf9/R6Gff/Lt+/A7i6fP9ligHOxgAvoRjeve3/3rLs2tIRQ0zEsHG77Xsb1s+S9Iby/XTgIIpEcOOO42zvypwMK4BPSfoEcK3tm1SMMnoIcH05/MFY4IE+zv1XigRwA8X4Pl8oty+nGIbgauDqAa7/KmAOcEd5rd0phr2G4tf4HRRf/Gc1nHO77dXw9DAjryyPeQnw47Kc3YBbgRcCD9i+A8DliK/lMY32phhS4yCKUXfHDxA3wFHAG8v3/wL8Y8O+q21vB+6U9LwKZcUwl0QQrfT4jjeS5lP8Oj3K9mZJi4AJFEOGD3bck608s5lzAoDt/5I0h6Id/B8k/QfFKJirbA80DeE15Tn7UnyZ/7DcfiLFBCavB/5O0sG2t/ZThoDLbL+/j337As+l+FKewK8/m95/u8tyrrf9pmcULh3ax/F9+Rhwg+03lM1siyqc01vjdZ5sDGMnyophJn0EUZdHgYlN9u8NPFwmgRcB88rttwK/LelAgPKLeKDy7qMcMljS4cCOc58PbLb9VYpmmMOBu4GpKuejLdv9D+5doIsZzG4HPktRm9hWttdPt30DxSQxkyi+zPvzA+AkSb+x42+RNLPcdyHwd8DlwCcazpmrYpTcMRQ1kpuBxcDRkn6zLGcPSS+gGDH1+ZKOKLdPlDSuj89qb4qpDKFo/tmh2Wd6C0VNCOBPyjhilEoiiFrY3kDRlLFS0if7OOS7wDhJyyl+sS4uz1sPnAZ8S9IyiiYaKNqs39BXZzHFPAj7qhj59F0U81MDvBS4vdz+N8Dfu5iq9CTgE2X5S+n/bqR/Bd7SEMNY4KuSVgA/Af7J9i8ldUl61hSSLuZs/luKWbqWU7T57y/pbcBW21dQdKofIenY8rRby20rgXuBq8rP5O3AlWU5i4EXlX/LycDnyr/leoraxQ3AS3Z0AlM06/yDpB+Xf8MOvY9rdBZwanm9twJn9/MZxSiQ0Ucjhomyuex9HgET08fokhpBRESHS40gIqLDpUYQEdHhkggiIjpcEkFERIdLIoiI6HBJBBERHe7/A3kx8RK+Iyp6AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# CORRELATION OF TRACT UNDER-USAGE IN OTHER TRACT'S HOME DISTRICTS vs. being near a boundary\n",
    "fig, ax = plt.subplots()\n",
    "plt.scatter(tractUse,nearEdge,marker='.' )\n",
    "ax.set(xlabel=\"tract use vs. expectation\", ylabel=\"number of unfilled wedges - max = \"+str(nWedges))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "6bb5c12a-a6a4-4cb1-9026-d227bc11c2ea",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.13857032468293676 = CA std dev of TRACT usage.  Here is its weighted histogram\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAEYCAYAAAAJeGK1AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8/fFQqAAAACXBIWXMAAAsTAAALEwEAmpwYAAASr0lEQVR4nO3df6zddX3H8efLFraBTjd7RUPRsoW4qbFIbooOg6CTFFE7E5e0c5o4TYcBo1viUveHZO4fF5NtUdGmwQ7NpGT+qDazAiZuw+nYestQQIF1tYZr3XoRFVETUvfeH/dbc7zc23O497Tnc859PpKTe76fH9/7/qZpX/18z/d+bqoKSZJa86RRFyBJ0mIMKElSkwwoSVKTDChJUpMMKElSkwwoSVKTmg2oJLuTHEtyzwBj/ybJXd3rgSQ/OA0lSpJOobT6c1BJLgUeBT5eVS94AvPeDryoqv7olBUnSTrlml1BVdXtwMO9bUl+M8ktSQ4m+XKS31pk6jZgz2kpUpJ0yqwddQFP0C7g6qr6ryQXAx8GXn6iM8lzgPOBL42oPknSkIxNQCV5MvA7wCeTnGj+pQXDtgKfqqqfnc7aJEnDNzYBxfztyB9U1YUnGbMVuOb0lCNJOpWa/Qxqoap6BPhWkt8HyLyNJ/qTPBf4NeDfRlSiJGmImg2oJHuYD5vnJplN8hbgDcBbknwNuBfY0jNlG3BztfpYoiTpCWn2MXNJ0urW7ApKkrS6NfmQxLp162rDhg2jLkOSdBocPHjwoaqaWtjeZEBt2LCBmZmZUZchSToNknx7sXZv8UmSmmRASZKaZEBJkppkQEmSmmRASZKaZEBJkppkQEmSmmRASZKaZEBJkppkQEmSmtTkVkeCDTs+v2TfkfdddRorkaTRcAUlSWqSASVJapIBJUlqkgElSWqSASVJapIBJUlqUt/HzJPsBl4NHKuqFyzS/y7gDT3n+21gqqoeTnIE+BHwM+B4VU0Pq3BJ0mQbZAV1I7B5qc6qen9VXVhVFwLvBv6lqh7uGXJ51284SZIG1jegqup24OF+4zrbgD0rqkiSJIb4GVSSs5hfaX26p7mA25IcTLK9z/ztSWaSzMzNzQ2rLEnSmBrmQxKvAb6y4PbeJVV1EXAlcE2SS5eaXFW7qmq6qqanpqaGWJYkaRwNM6C2suD2XlUd7b4eA/YCm4b4/SRJE2woAZXkqcDLgM/1tJ2d5Ckn3gNXAPcM4/tJkibfII+Z7wEuA9YlmQWuA84AqKqd3bDXAbdV1Y97pp4D7E1y4vvcVFW3DK90SdIk6xtQVbVtgDE3Mv84em/bYWDjcguTJK1u7iQhSWqSASVJapIBJUlqkgElSWqSASVJapIBJUlqkgElSWqSASVJapIBJUlqkgElSWqSASVJapIBJUlqkgElSWqSASVJapIBJUlqkgElSWqSASVJapIBJUlqkgElSWqSASVJapIBJUlqkgElSWpS34BKsjvJsST3LNF/WZIfJrmre72np29zkvuTHEqyY5iFS5Im2yArqBuBzX3GfLmqLuxe7wVIsga4HrgSeB6wLcnzVlKsJGn16BtQVXU78PAyzr0JOFRVh6vqMeBmYMsyziNJWoWG9RnUS5J8LckXkjy/azsXeLBnzGzXtqgk25PMJJmZm5sbUlmSpHE1jIC6E3hOVW0EPgh8tmvPImNrqZNU1a6qmq6q6ampqSGUJUkaZysOqKp6pKoe7d7vB85Iso75FdN5PUPXA0dX+v0kSavDigMqyTOTpHu/qTvn94ADwAVJzk9yJrAV2LfS7ydJWh3W9huQZA9wGbAuySxwHXAGQFXtBF4PvC3JceCnwNaqKuB4kmuBW4E1wO6quveUXIUkaeL0Daiq2tan/0PAh5bo2w/sX15pkqTVzJ0kJElNMqAkSU0yoCRJTTKgJElNMqAkSU0yoCRJTTKgJElNMqAkSU0yoCRJTTKgJElNMqAkSU0yoCRJTTKgJElNMqAkSU0yoCRJTTKgJElN6vsLC3XqbNjx+VGXIEnNcgUlSWqSASVJapIBJUlqkgElSWqSASVJalLfgEqyO8mxJPcs0f+GJF/vXl9NsrGn70iSu5PclWRmmIVLkibbICuoG4HNJ+n/FvCyqnoh8JfArgX9l1fVhVU1vbwSJUmrUd+fg6qq25NsOEn/V3sO7wDWD6EuSdIqN+zPoN4CfKHnuIDbkhxMsv1kE5NsTzKTZGZubm7IZUmSxs3QdpJIcjnzAfXSnuZLqupokmcAX0xyX1Xdvtj8qtpFd3twenq6hlWXJGk8DWUFleSFwA3Alqr63on2qjrafT0G7AU2DeP7SZIm34oDKsmzgc8Ab6yqB3raz07ylBPvgSuARZ8ElCRpob63+JLsAS4D1iWZBa4DzgCoqp3Ae4CnAx9OAnC8e2LvHGBv17YWuKmqbjkF1yBJmkCDPMW3rU//W4G3LtJ+GNj4+BmSJPXnThKSpCYZUJKkJhlQkqQmGVCSpCYZUJKkJhlQkqQmGVCSpCYZUJKkJhlQkqQmGVCSpCYZUJKkJhlQkqQmGVCSpCYZUJKkJhlQkqQmGVCSpCYZUJKkJhlQkqQmGVCSpCYZUJKkJhlQkqQmGVCSpCb1Dagku5McS3LPEv1J8oEkh5J8PclFPX2bk9zf9e0YZuGSpMk2yArqRmDzSfqvBC7oXtuBjwAkWQNc3/U/D9iW5HkrKVaStHr0Daiquh14+CRDtgAfr3l3AE9L8ixgE3Coqg5X1WPAzd1YSZL6GsZnUOcCD/Ycz3ZtS7UvKsn2JDNJZubm5oZQliRpnA0joLJIW52kfVFVtauqpqtqempqaghlSZLG2dohnGMWOK/neD1wFDhziXZJkvoaxgpqH/Cm7mm+FwM/rKrvAgeAC5Kcn+RMYGs3VpKkvvquoJLsAS4D1iWZBa4DzgCoqp3AfuBVwCHgJ8Cbu77jSa4FbgXWALur6t5TcA2SpAnUN6Cqaluf/gKuWaJvP/MBJknSE+JOEpKkJhlQkqQmGVCSpCYZUJKkJhlQkqQmGVCSpCYZUJKkJhlQkqQmGVCSpCYZUJKkJhlQkqQmGVCSpCYZUJKkJhlQkqQmGVCSpCYZUJKkJhlQkqQmGVCSpCYZUJKkJhlQkqQmGVCSpCYZUJKkJg0UUEk2J7k/yaEkOxbpf1eSu7rXPUl+luTXu74jSe7u+maGfQGSpMm0tt+AJGuA64FXArPAgST7quobJ8ZU1fuB93fjXwP8SVU93HOay6vqoaFWLkmaaIOsoDYBh6rqcFU9BtwMbDnJ+G3AnmEUJ0lavQYJqHOBB3uOZ7u2x0lyFrAZ+HRPcwG3JTmYZPtS3yTJ9iQzSWbm5uYGKEuSNMkGCags0lZLjH0N8JUFt/cuqaqLgCuBa5JcutjEqtpVVdNVNT01NTVAWZKkSTZIQM0C5/UcrweOLjF2Kwtu71XV0e7rMWAv87cMJUk6qUEC6gBwQZLzk5zJfAjtWzgoyVOBlwGf62k7O8lTTrwHrgDuGUbhkqTJ1vcpvqo6nuRa4FZgDbC7qu5NcnXXv7Mb+jrgtqr6cc/0c4C9SU58r5uq6pZhXoAkaTL1DSiAqtoP7F/QtnPB8Y3AjQvaDgMbV1ShJGlVcicJSVKTDChJUpMMKElSkwwoSVKTDChJUpMMKElSkwwoSVKTDChJUpMMKElSkwwoSVKTDChJUpMMKElSkwwoSVKTDChJUpMMKElSkwwoSVKTDChJUpMMKElSkwwoSVKTDChJUpMMKElSkwwoSVKTBgqoJJuT3J/kUJIdi/RfluSHSe7qXu8ZdK4kSYtZ229AkjXA9cArgVngQJJ9VfWNBUO/XFWvXuZcSZJ+wSArqE3Aoao6XFWPATcDWwY8/0rmSpJWsUEC6lzgwZ7j2a5toZck+VqSLyR5/hOcS5LtSWaSzMzNzQ1QliRpkg0SUFmkrRYc3wk8p6o2Ah8EPvsE5s43Vu2qqumqmp6amhqgLEnSJBskoGaB83qO1wNHewdU1SNV9Wj3fj9wRpJ1g8yVJGkxgwTUAeCCJOcnORPYCuzrHZDkmUnSvd/Unfd7g8yVJGkxfZ/iq6rjSa4FbgXWALur6t4kV3f9O4HXA29Lchz4KbC1qgpYdO4puhZJ0gTpG1Dw89t2+xe07ex5/yHgQ4POlSSpH3eSkCQ1yYCSJDXJgJIkNcmAkiQ1yYCSJDXJgJIkNWmgx8zVlg07Pr9k35H3XXUaK5GkU8cVlCSpSQaUJKlJBpQkqUkGlCSpSQaUJKlJBpQkqUkGlCSpSQaUJKlJBpQkqUkGlCSpSQaUJKlJBpQkqUkGlCSpSQaUJKlJBpQkqUkDBVSSzUnuT3IoyY5F+t+Q5Ovd66tJNvb0HUlyd5K7kswMs3hJ0uTq+wsLk6wBrgdeCcwCB5Lsq6pv9Az7FvCyqvp+kiuBXcDFPf2XV9VDQ6xbkjThBllBbQIOVdXhqnoMuBnY0jugqr5aVd/vDu8A1g+3TEnSajNIQJ0LPNhzPNu1LeUtwBd6jgu4LcnBJNuXmpRke5KZJDNzc3MDlCVJmmR9b/EBWaStFh2YXM58QL20p/mSqjqa5BnAF5PcV1W3P+6EVbuYvzXI9PT0oueXJK0eg6ygZoHzeo7XA0cXDkryQuAGYEtVfe9Ee1Ud7b4eA/Yyf8tQkqSTGmQFdQC4IMn5wHeArcAf9A5I8mzgM8Abq+qBnvazgSdV1Y+691cA7x1W8eNiw47Pj7oESRo7fQOqqo4nuRa4FVgD7K6qe5Nc3fXvBN4DPB34cBKA41U1DZwD7O3a1gI3VdUtp+RKJEkTZZAVFFW1H9i/oG1nz/u3Am9dZN5hYOPCdkmS+nEnCUlSkwwoSVKTDChJUpMMKElSkwwoSVKTDChJUpMMKElSkwwoSVKTDChJUpMMKElSkwwoSVKTDChJUpMG2ixW4+Nkv9rjyPuuOo2VSNLKuIKSJDXJgJIkNcmAkiQ1yYCSJDXJgJIkNcmAkiQ1yYCSJDXJn4NaRfwZKUnjxBWUJKlJAwVUks1J7k9yKMmORfqT5ANd/9eTXDToXEmSFtP3Fl+SNcD1wCuBWeBAkn1V9Y2eYVcCF3Svi4GPABcPOHcinOz22Tjw9p+k1gzyGdQm4FBVHQZIcjOwBegNmS3Ax6uqgDuSPC3Js4ANA8xV45YbvgabpJUYJKDOBR7sOZ5lfpXUb8y5A84FIMl2YHt3+GiS+weo7WTWAQ+t8BwtGNvryF/9wuHYXsciJuVavI72TMq1PNHreM5ijYMEVBZpqwHHDDJ3vrFqF7BrgHoGkmSmqqaHdb5R8TraMynX4nW0Z1KuZVjXMUhAzQLn9RyvB44OOObMAeZKkvQ4gzzFdwC4IMn5Sc4EtgL7FozZB7ype5rvxcAPq+q7A86VJOlx+q6gqup4kmuBW4E1wO6qujfJ1V3/TmA/8CrgEPAT4M0nm3tKruTxhna7cMS8jvZMyrV4He2ZlGsZynVk/sE7SZLa4k4SkqQmGVCSpCZNXEBNytZKSXYnOZbknlHXshJJzkvyT0m+meTeJO8YdU3LkeSXk/xHkq911/EXo65pJZKsSfKfSf5x1LWsRJIjSe5OcleSmVHXs1zd5gafSnJf93flJaOu6YlK8tzuz+HE65Ek71zROSfpM6hua6UH6NlaCdg2jlsrJbkUeJT5HTpeMOp6lqvbUeRZVXVnkqcAB4HfG7c/kyQBzq6qR5OcAfwr8I6qumPEpS1Lkj8FpoFfrapXj7qe5UpyBJiuqrH+4dYkHwO+XFU3dE88n1VVPxhxWcvW/Vv8HeDiqvr2cs8zaSuon2/LVFWPASe2Vho7VXU78PCo61ipqvpuVd3Zvf8R8E3mdxgZKzXv0e7wjO41lv+7S7IeuAq4YdS1CJL8KnAp8FGAqnpsnMOp8wrgv1cSTjB5AbXUlktqQJINwIuAfx9xKcvS3Ra7CzgGfLGqxvI6gL8F/gz4vxHXMQwF3JbkYLdd2jj6DWAO+LvutusNSc4edVErtBXYs9KTTFpADby1kk6vJE8GPg28s6oeGXU9y1FVP6uqC5nfEWVTkrG79Zrk1cCxqjo46lqG5JKquoj536hwTXdrfNysBS4CPlJVLwJ+DIzz5+dnAq8FPrnSc01aQA2yLZNOs+4zm08Dn6iqz4y6npXqbr/8M7B5tJUsyyXAa7vPbm4GXp7k70db0vJV1dHu6zFgL/O3+cfNLDDbsyL/FPOBNa6uBO6sqv9d6YkmLaDcWqkx3cMFHwW+WVV/Pep6livJVJKnde9/Bfhd4L6RFrUMVfXuqlpfVRuY//vxpar6wxGXtSxJzu4evKG7JXYFMHZPvVbV/wAPJnlu1/QKxvtXEm1jCLf3YLDNYsfGiLdWGqoke4DLgHVJZoHrquqjo61qWS4B3gjc3X1+A/DnVbV/dCUty7OAj3VPJz0J+IeqGutHtCfAOcDe+f8DsRa4qapuGW1Jy/Z24BPdf6wP020XN26SnMX8U9R/PJTzTdJj5pKkyTFpt/gkSRPCgJIkNcmAkiQ1yYCSJDXJgJIkNcmAkiQ1yYCSJDXp/wGrS1d3WGoaQwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# LET'S VISUALIZE OUR tract usage in a histogram\n",
    "n_bins=50\n",
    "avgTractUse = 0.\n",
    "statePop = np.sum(tractPop)\n",
    "for t in range(nTracts):\n",
    "    avgTractUse += tractUse[t] * tractPop[t]/statePop\n",
    "sumVarTractUse = 0.\n",
    "for t in range(nTracts):\n",
    "    sumVarTractUse += (tractUse[t]-avgTractUse)**2 *tractPop[t]/statePop\n",
    "sdTractUse = sumVarTractUse ** 0.5\n",
    "\n",
    "print(sdTractUse,\"=\",STATE,\"std dev of TRACT usage.  Here is its weighted histogram\")\n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "# We can set the number of bins with the *bins* keyword argument.\n",
    "ax.hist(tractUse, bins=n_bins, weights=tractPop)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "121f9869-3d25-4594-93b3-64a57a95aca8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.1314264544517114 = std dev of PRECINCT usage.  Here is its weighted histogram\n",
      "this is a histogram of PRECINCT usage by precinct for CA\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# LET'S VISUALIZE OUR precinct usage in a histogram  \n",
    "n_bins=50\n",
    "avgPrecinctUse = 0.\n",
    "stateVTDPop = np.sum(vtdPop)\n",
    "for p in range(nPrecincts):\n",
    "    avgPrecinctUse += precinctUse[p] * vtdPop[p]/stateVTDPop\n",
    "sumVarPrecinctUse = 0.\n",
    "for p in range(nPrecincts):\n",
    "    sumVarPrecinctUse += (precinctUse[p]-avgPrecinctUse)**2 *vtdPop[p]/stateVTDPop\n",
    "sdPrecinctUse = sumVarPrecinctUse ** 0.5\n",
    "\n",
    "print(sdPrecinctUse,\"= std dev of PRECINCT usage.  Here is its weighted histogram\")\n",
    "print(\"this is a histogram of PRECINCT usage by precinct for\",STATE)        \n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "# We can set the number of bins with the *bins* keyword argument.\n",
    "ax.hist(precinctUse, bins=n_bins, weights=vtdPop)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "f6f03dcb-c722-4789-b47f-fb7aa3be97bc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here's a look at numerical stability - number of loops, avg =  8.1221\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "avgTLC = 0.\n",
    "usedTracts = 0.\n",
    "for t in range (nTracts):\n",
    "    if(tractLoopCounter[t] > 0):\n",
    "        avgTLC += tractLoopCounter[t]\n",
    "        usedTracts +=1.\n",
    "avgTLC = round(avgTLC / usedTracts, 4)\n",
    "print(\"here's a look at numerical stability - number of loops, avg = \",avgTLC)\n",
    "n_bins=20     \n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "# We can set the number of bins with the *bins* keyword argument.\n",
    "ax.hist(tractLoopCounter, bins=n_bins)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "974631b2-10ef-4847-af2e-a1e26b6fa768",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this is a histogram of home-district pct GOP by tract\n",
      "statewide vote is off by 0.00204 0.35294 HD avg vs true 0.35091\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# LET'S VISUALIZE OUR HOME DISTRICT red-blue lean in a histogram  and check the statewide vote vs. HD average\n",
    "n_bins=50\n",
    "print(\"this is a histogram of home-district pct GOP by tract\") \n",
    "print(\"statewide vote is off by\",round((stateGOP2-stateGOP),5),round(stateGOP2,5),\"HD avg vs true\",round(stateGOP,5))\n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "# We can set the number of bins with the *bins* keyword argument.\n",
    "ax.hist(HDvGOP, bins=n_bins,weights=HDweight)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "720d9eb5-11e8-45f7-b402-a0048e9ddb99",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "calculated statewide Hispanic pct was 0.35224, should have been 0.35953\n",
      "this is a histogram of home-district VAP pct Hispanic by tract\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# LET'S VISUALIZE OUR home district pct Hispanic in a histogram\n",
    "print(\"calculated statewide Hispanic pct was {0}, should have been {1}\"\n",
    "      .format(round(stateHisp2,5), round(np.sum(tractHisp)/np.sum(tractVAP),5) ) )\n",
    "n_bins=50\n",
    "print(\"this is a histogram of home-district VAP pct Hispanic by tract\")        \n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "# We can set the number of bins with the *bins* keyword argument.\n",
    "ax.hist(HDvHisp, bins=[0.1,0.15,0.2,0.25,0.3,0.35,0.4,0.45,0.5,0.55,0.6,0.65,0.7,0.75,0.8,0.85,0.9,0.95,1.0],\n",
    "        weights=HDweight)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "1ab7704f-a226-45a9-98a6-d0684522c1eb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this is a bar plot of seats by VAP pct Hispanic for CA\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ALTERNATE VIEW OF HISPANIC VOTE: HOW MANY DISTRICTS PER 10pct BIN of PCT HISPANIC VOTE?\n",
    "n_bins = 20\n",
    "HispSeats = [0.]*n_bins\n",
    "binMid = [0.]*n_bins\n",
    "for b in range(n_bins):\n",
    "    binMid[b]= float(b)/n_bins + 0.5/n_bins  #centering each bin\n",
    "for t in range(nTracts) :\n",
    "    b = int(HDvHisp[t]*n_bins)\n",
    "    HispSeats[b] += HDweight[t]*nDistricts  #multiply by nDistricts to get number of expected seats\n",
    "\n",
    "print(\"this is a bar plot of seats by VAP pct Hispanic for\",STATE)        \n",
    "fig, ax = plt.subplots()\n",
    "plt.bar(binMid,HispSeats,width=0.09 )\n",
    "#plt.scatter(binMid,HispSeats )\n",
    "ax.set(xlabel=\"pct Hispanic\", ylabel=\"number of seats\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "3ef49161-368a-40a2-83ff-92187edb3462",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "using a threshold of 0.35 the number of Hisp districts should be 24.295\n"
     ]
    },
    {
     "data": {
      "image/png": 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/z8S2E6npXdPepikKGUrIc5mN5zfy9PKnaVOhDRWLVcRJ74SLwYW3W7xNhWIV7G2eIge4/+g+X+7/km8OfUNUXBT96vTj4zYfK0FX5BlKyHMZo8nIoDWDOBJ0hFhjLA+iHxAWE8YrDV7hp54/2ds8RQ4SEhXCl/u/ZM4/c5SgK/IUJeR5TEx8DGW/KouTwYkLb1zAxcHF3iYpcpikgv5CnRf4pM0nStAVuYZKP8xjnAxOLHl2CUHhQXy4/UN7m6PIBbxcvZjeaTpXxl5hfMvxrDu7jjrz6/DSHy9x6cEle5unKISkK+RCCGchxD9CiONCiFNCiE/N2xsIIQ4KIY4JIQKEEE1z39yCgaVbTU2vAuyh3T0Am9vCmnJwdLy9rcmXWAv6283f5tdTv1J9bnVGrBvBjbAb9jZPUYhIN7QitF5oblLKCCGEA7AXGANMBr6WUm4SQnQD3pNStkvrWoUhtHIj7Ab+C/3x9fDl0NBD6HV6e5uUee4egC1P2G5z94MWS8C7hX1sKgDcCr/FtD3TWHBkATqhY6T/SN5v9b4qn6vINtkOrUgNS4dbB/NDmh8e5u1FAVUfFOi+vDt3Iu/wZrM3qT2vNuJTQfW51ZmyewrBkcH2Ni9j7H0++baIC7ClFZxfCEBgILRrB8WKQe3asHZtnlqYLyldpDRzus3h/BvnGVRvEHP/mUvl2ZWZsHUC96Lu2ds8xWNMhiY7hRB64AjgB3wrpRwvhKgJ/A0ItA+EJ6SUV1M4dzgwHKB8+fKNr15NdshjRcMFDTl2+5jNtk6VO7H10lY8nT1Z1nsZXfy65O/mFct1aJ/TKSD0xLXdS802zXn1VRg3DvbuhZ49ISAAqlfPU0vzNefvnefTXZ+y/L/lFHEqwtvN3+atFm/h4eSR/skKhRU5mrUihCgGrAHeQBPnXVLK1UKI54HhUspOaZ1fGEIrUXFRHL55mODIYFwcXHjK7ykMOgMng0/yzIpnuPzwMg1KNeCLzl9wN+ou1UpUo1HpRvY225blDkB8qrv3xC+h73svEhQEOvPnUf/+mohPmpQnFhYoTgWfYuLOiawOXE1xl+K898R7vN70ddwc3extmqKAkOPph0KIiUAk8DFQTEopzXH0UCllmq5GYRDytIiOj2bZiWW8sekNHsU/stm3edBmOlfpbCfLkrC5LYTsTnX3L8Fb+OKH2hzecSUhZj5sGKxfDw8fQnS0dpwQ0KcPrFqV+yYXBI4EHeGTnZ+w8fxGSrqV5IPWHzC88XCcDc72Nk2Rz8l2jFwI4W32xBFCuACdgDNoMXFLgZEOwPlsW/uY42xwZkijIdx4+wYbBmzgn6H/JOz7v33/Z0fLzNw9AKemQ6WBaR5W5v5nXL8hMG3tBHcPEBcHK1eCn58m4mXKgIsLPP88/PYbfP99Htmfz2lcpjEbBmxg36v7qOVdizF/jaHqnKosPLJQNf9WZIuMBGpLAzuEECeAw8AWKeV6YBjwpRDiODANcxxckT7FXYrTrWo3mpRtwqKeiwDoXNnO3vjdA7CtPRz/EI68CV5tUj20md8B3JwimfnnG8T91Z75Q8YSGWGion41IKlSBWJi4JdftOOHD9e8c1/fvBlKfueJck+w/aXtbBu8DV8PX0asH0GNb2uw9PhSjCajvc1TFEDUys58QLU51dAJHeOeGEfDUg1pXKZx3hvxzyi48F3ie+82cDf18MraI90ZOG8ZEdFFANDr4qnne4Kj1xrx8eBf+GzJC2jz4KDXg9GsTy++CEuW5NYgCh5SSjZd2MRH2z/i6O2j1PCqweR2k+lTq0/+nhBX5ClqZWcBoF+dfpy9d5Zh64bRY0UPe5ujYYwmxT8PhxLExRt4++evcTTE8WmfT/hiwDsYTQZOXK8HwIXzseaDNSfBaAQhtIzV5ctUQw5rhBB0q9qNgOEB/Nb3N3RCx/O/PU+jBY1Yd3adamCiyBBKyPMBk9tP5s64O/i4+RBrjLXPP2+lwaBzBIT2XGUI6J1I/BPRgd4FGkzj4MWWPIj0xKCL46NeU3mjy1zcnCJwcYwCYMWBQTaXFkLi4fIQAKMJPIoYcXMDNzeVg25BJ3T0qdWHEyNP8POzPxMRG8EzK5+hxY8t2HppqxJ0RZooIc8nBIUHERwZzMdtPkZLAspjvFtAx51Qf6r2XHU4dNgGfsOhbC/tucM2AuOHM2LpSh5EFSPsUVHWH+3OxTtVcHF8RESMJWkp0X4hwNHBSPgjd/MWiXexMJ56CqKjJWcCTfTsKRECm0ffvnk5+PyDXqdnYL2BBL4WyPc9vicoPIjOSzvTfnF79l7ba2/zFPkUJeT5BJM0AeDu6J7OkbmIdwuo/b7tMvzLi+HmOri8mLi7J+nR6RatqmyjmGsozg6P6D93GV1m/E3Yo6J4FwnGUR+N9WIiKSUlPMIwSQMApYvdIiLajWNHotGLWBz0MZYjbUz57TcoXrzweusOegeGNhrK+TfOM6frHM7eO0vrRa156uenCAhS80wKW5SQ5xNqe9emWolqjN44mmY/NMsfS7qDd4IxFjCCMYaDK38mIlIwe+CrFHN9gE5IShW9ze2HJYmNdyQi2p1Pn5tIUlEOCvE0v5I8Ue8qnm73ePjACEhi4p1Svf2DB9pCo7Nnc2l8BQAngxOvN32di29eZGanmQQEBdDk+yY8+8uz/HfnP3ubp8gnKCHPJzgZnNg+eDsv1H6Bf27+w5cHvrS3SeDTDvSOIPQgdAQ9KEW5Etdxdoxl3bhnqFw6iEt3/YgzOgJQosg9KnlfBgQ6YcLdOZxuDTYA0KD8UUDwTK153A52oajTHeKNDuiEyeqGEr3OhF6nbdPpoHJlWLEiT0edL3F1cOXdlu9yacwlJrebzPbL26n/XX36r+7PuXvn7G2ews4oIc9HlPUoy5Jnl/BivReZsW8G+6/vz5kLn18IfzWDXc9q+eJWpFn8yruFFiev9xn4f0uZ4sFcv1cOk0lQ2/c0+/88iIuLwGAQ+HjFsWjkcF5ZuBi9zohJCqJjndh5uj16nZHTQbVwc4rk+r0KuDpGcuO+LxIdAmshNyEwYpJahoter4n5zZs582N4HPBw8uDjth9zecxlJrSawNqza6n5bU1e/fNVrjy8Ym/zFHZCCXk+ZG63ubg7urPgyILsX+z8Qjg8Au7/Azf/gK1tEsQ8Lg569IAnn4TgYJgzBwYOTBLKsMTNqw6n2fDpuLnBzO1ziGuwkPlbh/HoEZQqBfEmRw7JBVQsF4nRpMXDJYKoWFeMJj2x8U5Exrgx668xhD3yIM7oAIBRWpf51RFvMiCl9mfp7Q0mE5Qtm/0fw+NGcZfiTOs4jctjLjOm2RiW/7ecanOqMXrDaG6GqU++woYS8nyIQWcgIjaCSsUqZf9i11fbvpfxcFlbkXPwIEREQFHdRZycTHTsKImIgBo1oGjR5BONjmWbs3ZzKTZdfA2vFsOYOROqVIG//tJCIBNnViDwojda1orEaHKw3DThGiHh3rzXYyY1Sp8xb0n5T1AIyd3gWE6flnz1lUpTTA0fNx++6vIVF9+8yJCGQ/j+3+/xm+PHO3+/U3DKJiuyjRLyfMjJ4JOYpIkKRStk/2JO3qnuCgqCMj4RvP5+ZRJTBjXRDQvTaqUknWisXRt27YLQUC12HREBNWvC4cPw33+aF62R+Kfl7hxJae8oczxcMnnNRMLMK0I1v13i43HH5j5SSkwmQb8WvxASeDDZt4X167VwkBDg7AwfFvKuemU9yjK/+3zOvX6OfnX6MevQLCp/U5kPt33Ig0cP7G2eIpdRQp4PqelVE29Xb+Yensv5e9msRRZzN9mmwH3HaFd7L0NfjuLYSdeE7W5OkbT1v5bwXqdLe6KxWTNtUc/MmRAVBZ06aQLfrRtY55IvmR9E+cpuCJ0eEBhNeh7Fe/LaUz9Rx/ckEkFwWEnmTLuMlAK5sze7P26HV5F7LB05iItHTjB5sla/pVUr+PprLSQUGmoeYgxMmwYTJ2bvR/U4UMmzEot6LuL06NP0qN6DaXunUembSkzZPYXwmHB7m6fILaSUefZo3LixVGSM5SeWSyYh3ae5y4PXD2b9QucWSLmMhEfsYoOsUvK8nPr8+zL8R1fpoIuRYJJgktVLn5XubvHS0VFK0B4ODlK6umqPWrWk/PNP28ufPCllmzbafr1eyt9+k3LOnMTzQcqYGCkrVJBSp0vcJkTi9WrWlNLDQzumaJFoWavsSTnu6RnSv/I/mr2+d+XUN3fIcaNvyKeeSryGp6eUL78spbOz9l6nk/LMmWz80B9Djt8+Lnuu6CmZhCwxo4T8fN/nMjI20t5mKTIJECDT0FYl5PmYgJsB0mGyg2QScuruqVm/0N6BUi4TUi5D7v64lSxZ9JY8+X81pX/lQxKMCUIuhEnWqmUrwtYPg0ETzZTEcuVKKf39tdfh4ZqoW84rUSL5tRo2lHLbNind3aX09U0UYhfHR9LJECWFMEp354dy50etZcmit6RxqV72f2K5fLn3GanTafaW9I6RRqOU/fppHzhJ7+HllfyDp7By6MYh2WVpF8kkZOkvSsu5h+bK6Lhoe5ulyCDpCbkKreRjLPWrAb488CV3Iu6kfOD5hbC9i/ZsqSluSTM8vxCu/ZpwaNCDMpRwD8H/4yMcueSPu3NEwj4pRYqpfh7mlffx8Vq98Tlzkh9Tpgxcv65lmbi7w+rVid2D7lmtbTIYtO3nzkHLluDvDzduaLFuV1dwc5PExDsjJUREe/DOsi8oW/wGu8+0Yt2/3anr8h1Oeq0ph6/7Cc7+/St792oZOEkJCdFa0FmW/Ts5Fd4J06Zlm/LXoL/Y9fIu/Ir78fqm16k2txo//vsj8abUu0EpCghpqXxOP5RHnjXmHporxSQhq86uKvdc3SNNJlPiziShE7ncQcpleilXumj7lhts9m//oK3UiXjpaIiSkBhW0R4pe+JTpkhZpEji+1q1ktsYEyNl5cpSTp8uZWyslDt2aN52YGDiMStXStm4sZRly2revZOTFpKxhFp0Oi1cUqdaiKxV/oL524JRCoyyZplT8vexveTuj1tJvUhqd9r2J3106ZLrv7J8jclkkpsvbJZNv28qmYSsNqeaXHVqle3flSJfgfLICz6vNX2Nvwf9zYPoB7Re1Jra82ozaeckTgafRF77zfZgGQcYwRSrpR5KW29LmichY+MdAAcywvjx4OiY+P7+/eTHODpq3u6mTeDlBaNHa3XHa9RIPKZMGc373rQJGjTQPPyoqERvGcDBAbr1KkGMQxW8ikVTzDWUYm4PGdx6Cd0brue/67UwytTszliFwL//1rz/wprSKISgc5XOHBxykD9e+AMHnQN9V/Wl6Q9N2XZpm73NU2QBJeQFhM5VOnN17FW+e/o7fNx8mLxrMnXn18Xrn/38HWl1oHDQltTrHMGzQbLr3A3zoWTRO4A+2b7UGDXKVrw9PVM+zjo18fRpePZZ2/2WLJcNG2D/fvjxR03EpYTYWO3Z1xcCArQwjUcxgZMhlg61trPpeFe8RobwxuJvra6YknDLFB7JcXZOZQFUIUIIQc8aPTk+8jj/6/k/giOD6bS0E52XduZI0BF7m6fIDGm56zn9UKGVnONm2E35w5EfZKVZlWST2RWl3PakFkoJ3i/lyWkJz6dn1pBta+6QRV0fyFplT8ppz4+XRV0e2ExypheWEML2/WuvZd1uS5ZLkSLaBOULL0hZqZKUrVvb3u+NN7TwS9XKUXLi0HVSrnCSuz9uJV0cIqRBFyNdnSLk7i9el04OUbKoS0gqoZa0x2cwaNky/frl3O+lIPMo7pH8+sDXssSMEpJJyL6/9pVnQ87a2yyFTD+0ooS8gDPn0BzJJGTAzYBk+2JvHkhINYxZ7CC3fdBeujmFSR+P21ZCnrG4siUV0dnZNu5t4fRpKdu2lbJo0ZTTFJOye7eUJUtKaTRq4m4t5AaDlOXKSenoqMXQ16+Xsu0TD6Wrc6w06OMkmKROmGTklQOyqMv9FD6UMi/qzs6pp1gWNkKjQ+Un2z+RblPdpP5TvRy+dri8EXrD3mYVatITchVaKeC8WO9FXB1c+S7gu2T7Dl5sToSxDBN6am3ZOtTeQY9G63m26QbzEak3sHB11eLc/v4kFK8qWRKWL7eNe0MGa7YkISgIypXTrlu7NuzeDUOGaPF1KbVCWd7e8L//wZgx8OTTRVm3wQE3dwMgMElBz34+FHF+mOY4UiZ52KVMGc2W994r3OEW0Apzfdr+Uy6NucToJqNZdGwRfnP8mLB1glolmk9RQl7AKepclAF1BrD85HJCo81LHc0piEFHtlLO4xQ6ohOOr+B1FWO8kQndp5LW5GB8PKxbp8W5o6JgyxZ4+BBq1Up+rKVmy4QJ2qRnhw7QvXvaq0Kt0xUtREXBa69p9zYatYnRUqUSr92qFZQoARUqaGmMWw9W4saDigC83OYnnAwxaY7JmlIe182vtOMvX9aE/K+/0re9sODj5sPsrrM5+/pZnqv1HDP3zaTK7Cp8uf9LouOj07+AIs9QQv4Y0MWvC1FxUaw6vUrLG9/SCo5/QJn7nyaUnbVwLaQ8ZYvfpFvDzTgmdOexxdUVPvlEm4DMiDhbe9cWKlRIu/ys9fL+uDjYuVP74OjXL/VrWzJjTCZtkrRmTcGU969RskQkuy8/x4g++6lW5lKGfma3w8pZvZN4FoujZUtYuRJ+/x2++cY2oyXNcr+POZU8K7H02aUcHXGUZr7NGLdlHNXnVmfp8aUJna0U9kUJeQEnOj6adza/g6ezJ81dnSFgFJhrfDfzO4SbUyQz179HXLyBnafbsu5oD/q1WEkzv0P4et1h7Fho3VoTVSFg9rRLRP4zHT+fcxkW55S862vX0i4/m5F0xZSuXbu25pl/8IGWGfPupArondwJflCUmYs70OclP5vzRboeunbh+w90bNqkhVtiY7VvHz17atUdsxI6ehypX6o+mwZuYuuLW/Fy9WLwH4NptKARmy9utrdpirQC6Dn9UJOdOc+VB1ckk5Cvb3hdy1axXhy0DHlyRi3ZpsZO6eHyMGFRTcK+mfVlmxah0sNDyprVIuXvM+ZLucJRymV6uXtix4Ql8Ba6dTPXQylqOymYkcVAWSWla7u6StmkSaIdL7+cWOvFkvViMFgmMjM6AZp6Fo+Dg3ZtD4/EcffrJ+XEidkfX0HFaDLK5SeWy0qzKkkmITst6SSPBB2xt1mPLaQz2Sm0Y/IGf39/GRCgGsfmNJ2XdmbftX2ED92MfnsH86KgDCD0Wvcfn3awvSMYExsnx8Y7UfO9swx7ZjfvTKrKrtPNefJJbeJxxgzYu1fzWAMCoHp1zbsePFjLIXd0hLffhunTc2Z8p05pHvuxY5qH/uABvPkmjBun2dG9u1YB8dVXNTvi4rRjNDLy920i+ZfT5BOoJ07A3bvauPv312T++++zNbQCT0x8DN8FfMdnuz/j3qN7DKg7gCntp1DJMwdq6SsSEEIckVL6p7ZfhVYeA0b5j+JR/COW374MnXZB2V7gWlFbHJSADltxEtqiIZ92Vk2WZcI+R0MMa9/uxqY95fHyq8nQV6IpWhS+/DJ5zDwuThPu997TBHXTJpg7N2uhh5Ri0dYLjRYu1I6zjt03b66JakSEtlgp3FyttUMHyEhGi49HSg0YbBcVCQFdumjhlYgIWLRIey7sOBmcGNN8DBffvMgHrT5gTeAaqs+tzlt/vUVIVIi9zSs0KCF/DOhVoxeNSzdm/NbxhHvUgbZroNdl6B8LnfdD/WnQZD7onc2rPp3Ab4TWj9O7hSbm5lrhCAdw9AKgtu9pdn3cjtAfijHj5a/wqxiRYsw8K1krKWGJRZcvr70/fVrzfkeOTDwmKEiLqXfokCj2kZFaR6PAQO3Dw2jUjnVNKLUuEh5Fiwp0Ost7jXvhxdO1TUpJcDAMHw5FPeKJj5f88otk/vzMjfFxpahzUaZ2nMr5N87zUv2XmP3PbKrMrsL0PdOJiouyt3mPPUrIHwN0QsfsrrO5FXGLX079YrvTqudmQiPljjug6XxtXwJmYRM68KiZ7B5lxF9cvxyB6U5i82bLhGZWslZS4uBBzZtesQKaNtVeN2gACxZoXj6Ajw+cOQOdOydOPB45on0TOHgwMR8ctCqMSQkNtZ6U1cbs6JCxUJTRCPPnS8LCdIDEIOJ4801ToZv0TIuyHmX5/pnv+W/Uf7St0JYPtn9AtTlalUWjyWhv8x5blJA/JjT3bY6Hkwf/3vo38ycH7wRTPCC1IlvFaiUJy0Azv4NaBszk28nSBbOStZISQUFaDRSTCTZu1IS4Sxcto2bGDO0Yy5SOpTStTqc9Gwwwaxb88Ufi9X79FQYNSu+ugkexbhmyr7jZcZcIijiH4+l+D6Mx5bK+hZ1a3rVY238tu1/eja+HL0PXDaXed/VYf249eTkvV1hQQv6YoBM6mpZtysqTK1kTuCb5P8vdA9qE5vGPtee7iZ41Pu1A75hYbKvSYC3WXn+aFm8HHA1xrH3nGTbtqYSXZySjhz5ISBfMaE54epQpo00mOjtrwgzaB0KxYnD7tvb+2DGtUuInn2jHvfhiYmrgpk1au7kKFbRQi8kEP/+c8r3699di6xlHJBQO04k4XByjCQn3oZiHkf37MzfOwkTrCq05MOQAv/X9jThjHD1W9KDd4nYcunHI3qY9Vighf4yY23UuJd1L0vvX3rz858vcjriduDNhQtNc4jZ4Z+I+7xaJYRdL3NwSO3cpZfbOBbXLnWPXhIaELnTn9OTiPFtHm3lMmhM+ZIgmps2bZ27xTLNmWlz70SPtYflAkFJb4RkXB//3f1pzC3d3LZwTEqItXKpTJ3FC9MwZzY6pU7WQy7Zt2geNpVSuwQBDh8Lx45Y7pz0h6uzwCCG0D0YhBD5ekuAwH/NXgoyVAk4gaeOPQoAQgj61+nBq9CnmdZvHmZAzNP+xOX1X9c1+T1qFRlq5iTn9UHnkuU+cMU5+vP1jqf9ULw2TDbLrz13lV/u/ktcv/aE1m1hubjoRvD/tCwXv145bppdyhZOUh0ZKuampbZ76tieTnRYbK2WVKlJOnarlgFvauWW0l+Y//2h54Hq9lNWrS/nKK1ou94YNUm7fnpjPXbFiYlMKvd42Z926IJeFfv2krFs3MTe8Rg0pf/01saGFh0faOecuTlHS0SE+4Xy9XivsJUQmqkFa/0wz8jt4TAmLDpOTdkySblPdpGGyQY5eP1reDr9tb7PyNWS3aJYQwlkI8Y8Q4rgQ4pQQ4lOrfW8IIc6at8/M1U8cRYYw6AxMbj+ZwNcCGdNsDBcfXOTtzW9Ta+WLrCg33tbrTgtrD17Gg1t5qDLE9phyfZKdlt0MliZNYM0azeM+exaWLdPSGrt10zxuIRJbzxkM2sNo1LZbSG3ytV69xPd9+8L27eYlQyYICwMQCAHFPKJxcrSdmHPSR+HqEIqWcy4xmSTXr2vnp1R/JkXS+lZUiCjiVISJ7SZy8c2LDG80nAVHFuA3x4/JuyYTEatyOrNCRkIrMUAHKWV9oAHwlBCiuRCiPdATqCelrA18kXtmKjJL1RJV+eLJLzj7+lnOvn6WeiXrMWDLJIZcuEBs8cbpXyBp3NynnZb50mQBlHpSe646PNlpOZHB0rOntkReSi00YpnohMQmFBcvamGUqlW1GLr1B0Vqk69+fvD119r7zz6D774DFxft/RtvaNUWixQRPAxzoXsPA26ucbSqvguAh1HFeRjliRASvS4ei6C//rrWQSlDmSsp/UwLMSXdS/Lt099y+rXTdKnShYk7J+I324/vAr4jzpjBRW0KjbTc9aQPwBX4F2gG/Ap0ysz5KrRiP+KMcXLClgmSScjP932esZOsm1RkkJTCGv3758xy9m3btDBImTKJy/UNBikbNpRy6NDE49IrGWBpbuHhkVhywGiUcvHipHXKbcMrbzz5tazsfd78Pl7Ofv8vKWUml+tn4WdaWDhw/YBs/VPrhD6iawLXqD6iZsiJxhJofcGOARHADPO2Y8CnwCFgF9AklXOHAwFAQPny5fNy7IoU6PpzV+k21U0uO7FMRsZG5vj1s1p3JSONKWJipPT21sS8SBEpy5fXGkI8/XRyIbUW65o1pfz995Tvu3KllP7+2uvg4LSFvIR7sHRxjJQ6ESefb74qQYzHj7f9IFFkHZPJJNeeWStrzq0pmYRsu6htik1TChs5IuQyUZSLATuAOsBJYDbalH9T4DJotVtSeyiP3P7cDLspGy1oJJmEdPzMUX77z7c5fo/0RDSpaK9enfEJ0qNHNfF2ctImLCdPzl6BLutvEGPG2Ap5sWLJxXzaiJXS1TlGDhmYODmXU984FInEGePk/MPzpfdMb8kk5KDfB8lrD6/Z2yy7kaNCrl2PicA44C+gndX2i4B3WucqIc8fxBnj5OYLm2XnJZ2l/lO93HVlV67dy1q0Le3bLEKp00k5YICULi5SliiRPMskNXHMqLedEay/QbRsaSvkSXuVgmarq6uUHTvmfKVHRXJCo0PlhC0TpNNnTtJ5irP8YOsHMiw6zN5m5TnZFnLAGyhmfu0C7AG6AyOByebt1YDryiMvWIRGh8pqc6pJ92nucvqe6fJe1L0cvb51KuKDB5pwW3pyli6dKI4Gg5Senrbnjh8vZZ8+mesDmlX+/FO7R2q9Si12g5b26OCghWNy4oNEkTGuPLgiB6weIJmE9PncR353+DsZZ4yzt1l5Rk4IeT3gKHDCHE75xLzdEfjZvO1ftMyWNK+lhDz/cSP0huy8pLNkErLUF6Xkiv9WZG2CKYVJPOuwxZw5yb1dnc5WJE+fTrzcCy9o4p7VfPSMYvmwGTAgaRgl0S4tx1x7ODlJ2alTztqQLQrZ5OmhG4dkq59aSSYha39bW248t7FQTIjmeGglOw8l5PmXI0FHZN15dSWTkAsDFmbu5FQWulgmEk+flrJsWVsh1+sTt+n1mqBbhytcXKT08sp4uCWrWD5salSNkGCS47pOTVHMQUo3N22CdfRoq28K1SPln3N+tY+QFtIFRiaTSa4+vVr6zfaTTEJ2XtJZHr993N5m5SrpCblaoq8AoFHpRhwdcRT/Mv5M2jUpc7WkU1noYsnn7t41mvqVz2Hd5MHDQ8s5B21BT/nyWgMJS9u3UaOgYsUs5KNncgm8Je/9QYjWv3R1gFYgxs0peXPhyEgtH33ePEs5AMnVy/E8++azeJSvTe0aUXnby7OQLjASQtC7Zm9OjT7F112+JiAogIYLGjJ07VBuhd+yt3l2QQm5IgG9Ts+sLrMIjgym45KOtrVarEkqlqksdGnWDPQiluDbcYxqMtZ8sibmlgU/oC3ocXeHESO0RT6nT0OvXlmoqJhWYbBUsHzYVCtzGYAb930B6NliR7rnAkTGFsEk9YRHF+HyVT0vvJDLvTytf/aFfIGRo96Rsc3HcuHNC4xpNoYlx5dQdU5VJu+aTGRspL3Ny1NUqzdFMtafW0+fX/tgNBlp7tuchqUa0sWvC139uqK/94+5LVysJiKNZkHsPXAsoT37tEtY/h8YCN073uLSrVIIIRFITNK2U5Gbm1YEy8lJqytuab4cGws1a8KwYfDOO7Bvn1bl8PDh5A2aEzg1XRNxjIlt7Gq/n+ZYLffp2/EoM75vkLDdwWAkLt6Qzk8q+f+OTicYNUrrkJTjWD6oLD/7Dtu07cE7bX7uhZUL9y8wYesEVgeupkyRMkztMJXB9QejEwXfX1Wt3hSZpnu17hwfeZzxLccDsOjYInqs6MHA3wcSd3tb4td5YwwEvK6J579jbcQkLg56dIumY431+HjcYWa/cZikDg+XcKpVjsLTIwqQREZq4ZSff7YV6KQVFUePJqFsbqpkwUO13OfA2YYY9InCnL6IQ/KqiQKTCa2sbUZDPJkJBaUUSrE0DinkIg7gV9yP357/jT2v7MHXw5dX/nyFxgsbs/3ydnublvukFUDP6Yea7CyYRMVGyc92fSaZhGy9oL4MXOykVVFcbpBymU6rhLhcr1VINGdQ7N4tZckS4fLRImdZ2eeCHNJ2gRQYZY3SJ6VOxElnh0gJRvlUh/vZts9mgVE2Jh9jYrT0QtAyZlJLR0x99ae2rWa1iIxNQmZ2stJyfEYrWBZijCajXH5iuazwdQXJJGT35d1l4N2Cm+yPmuxUZBcXBxc+avMRS3ot4cT9K9S7auQTfRuiG84CvZPmAQs9XFoExz+ELa0I2jSJcqWjcHYRrH3nGfadbwXA+TvVcHaIoZL3FZ71/xNfz6vZss3S5/PJJ82t3+a5MvD9vpy9n46HmoIn7OgI69dDlSrw4EFKJ8kUHkn3g94UkbFJyMxOVqZUNz4/kA9rrOuEjv51+3Pm9TP8X8f/Y/fV3dSZV4fXNrzG3ci79jYvx1FCrsgwL9Z/kXNvnOOFOv34LHAHfhun0ye2GRP1bTnj86wmRkjARBnDNq5fN2FqMIvaDbxYOGQETg4xfNhzGpGL3Dn9eW2cHWMpW6lEtmzKUtncNCZFa/sc4MKf04m5cZDSpSF10U4dk65IxkI8WZmszG+hlCxMMOclzgZnxrcaz4U3LjCi8YiEkrmf7/ucWGOsvc3LMZSQKzKFj5sPS59dypYXt9DMtxmnw24zOXA7rQ//jdFK65r5HdJ6fM72Jq7ODKJNJYiJdyIi2p24eAM7T7dj3bGe9BtSLlv2ZKlsbmqecIIofYTj7tZsmf0VPh5BmbLHyQmc3Fwz5jnnVw87MxSQFEhvN2++ffpb/hv1H63Kt+K9re9RZ16dx6aHqBJyRZboVLkTq59fzfGRxylftDwujkUQFfon7Lfp8elXkzGLpvH1oLEEXPbHa2QIo/83jyXfXk178jIDZLrx890DEHkNdIbknnDwTm0CFxPIeGrHvsP1OZVwMjzKkC3lywtiY+GJJ0jbc7YOReQ3DzuzFLAUyJreNdkwYAMbB2xEJ3T0WNGDrsu6Eng30N6mZQuVfqjIFsv/W87A3wfyW9/f6CPPwfEPbA9w8YVHN5KfKBy0Bs/ZFLBMpSlap+/p9FD5Va3RtMWGuwdgaxutI5IVS/YMYsjCn4g3pZzJohfxODnreBStx8Fg5PjqH6jRvF7qIp40hTCjP4O7B/JnqmF+tSsd4oxxfHv4WybtnEREbASvN32diW0n4uniaW/TkqHSDxW5ioeT1ndtz7U9xJVoBTon2wMepRLjkPE58jU8U2mKScMAj27bCo93C/D/1txsWst3D7xZgx93DsUkdfh4BLN6TG92fNged+cI1r7TA/9KASAE0dFQxieClW8MpEb4a7CtPfwzKnnMOKuhiPwci87pbxV5NHnqoHdgbPOxnH/jPEMbDWX2odlUm1uNBQELMJqM6V8gH6E8ckW2kFLy+sbXmRcwj5peNfm00UCeFdcwPDwG9wPQWqKlQEoeeW57dncPwNa2IK3aiKXUss5sR5zwomaH9rza9ie61d/I4O8W89/1elT2ucgXA97l2SZ/2J5X6km4vQ2wiIAAYQD/uYn3sAiyKVYLRaTnkZ9fCBd/hPgICDsDmDK82KlAkp1vLNnk2O1jjP1rLLuu7qJeyXp889Q3tKvYLk/unR7KI1fkKkIIvn36W/544Q8Ant/8ESV3/8ZLD0sw86GO70IFATH65CfqnOHhf4meV154nN4twN3PdtvFH1M+rvb7HLw3jAhTeSa89ZAGLStx4rfv6PfsPV7sGkCNMmdoN2UHxYY9oPZ7J1n7by+tGbXekcSFQlL70Ah4LXE8aU1wJvVEzy+EwyPg/j8QdhrtQ1FXIGLRWcaOk6cNSjVgx0s7WNV3FaHRobRf3J6+q/py5eGVPLMhq2Rk+ZpCkS49a/Ske7XurDu3jt9O/8aGC3+x5JEWa3bUCaIqg956IaQxXBMpdFoueqWXUl61mNM4e0O41cSW3jnVQ4OCoFwFR3TN5yVsq1ANrl9vT48vm/Bq25/YPKELe2+Poufk3wgYpqd6h7pweQlc+J4Ez1yabMfj3SL52FLyRK+vTm5UqU5Qd1LefpPJSyyTp5ZvLHn8gSWE4Llaz/F01af58sCXTN87nfXn1jOuxTgmtJqAm6NbntqTUZRHrsgx9Do9vWr04ufeP3P33btEvB9B9RLVKeZSHH2JpqmcZQLjI7j4AyBzP/uhaK2031uRWkaMybEkEaZyTPjIHceuO+nw3iy6P/mAFd/s0Q5qOh+azNPCKpYPqvTGk5InWq6P7THCkLKI59fYeVbIJymZlkVwZ18/S++avZmyZwrV51Zn37V9drEnPZSQK3IFIQRujm6UK1qO4MhgngrxhOKpiTnmTBETeNTN3X/gSoO1DwqE9lxpcKqHNmumFfWaOVNbQbpzJ6xbB3Xrmj31uuYJvrsHqGD8HzcDzyaKadXh0Gk31J+SsfH4tCPwdl3aTdlJkVfv49L4PUS14YiBpoSHx7AI1v5yw1asczoUcfeANkmb0kRtXpGPUjJ9PXxZ1nsZe1/Zy83wm8w9nBvV0LKPEnJFrrL6eS08cDX0KhRvZLtT7578hPDTuWuQdwvouBPqT9We0xCL1DJimjRJ4qkH7+Ta3bKULX7DVkwzIUhxd0/SZfp6roZUJDKmCNEJ8woCS8w9PNKR58b25OzPI9MtIZwl7h7Qsm0ufKc9trbW4vQKWpZvSYWiFRDJCqXlD5SQK3IVDycPqnhW4UzIGcadOUCMdRKLMSL5CabY3A8RZEJga9e2NJHQ6qQ/2+oAzYrMwM05OtFTP/8M6452p1+LVVkT0/ML2btsGUH3S9KgfIC5TrttNplAohNG4owOzNk03PbDIruhCMsk6+Ul5jILZqRRq25Z0MM1OURUXBT/Bf/H2ZDcLDifNZSQK3Kdvwf9jYPOgS8vH+d4bAoZLEnJaoggt/OPzfFox9Mfsvb1lmxaG6Z56h/UZsn8IGp0HWQrphm15/pqdp1pixCSv493SfEQicAk9YBk//knbD8sMvrBlJI91jH2Sz+Z4/rWNzbm22X3ec30jtO5FnoN/+/9CQrPXOmG3EYJuSLXqVK8CtVKVKOGVw2a1B5KsjreQg9ebbTFRNYhgswIc15M+lnFo2uXPc6u779N9NRfrm4rppmwJ/DBk/xv98vEGw08irfOirAu1iUSnkPiatKubwuKFdO+MWSovZzZnsCNy2jawgGDQaLXQ/l6tVj7z5OAURPtKkOgbC/t95DRidpCwpBGQ9j/6n7ijHF0WNwhX9VpUUKuyBMiYiMIjwknxLVqYjYHekBoAnL/EDSenRgigMwJc17kH2cmHp2CPYGB0K5lKMU8orX+nkvPELftOXq81pOOtbeh5YmnJAzWYi64ectZK9t76iBz3lnOwAFGm/ZygYHQrp3WQq98eW3CVvg0x2HAA+qOP8rhi40xGrUY//XbHvT66nfmbx2dOPnbdg102pPxidpCRG2f2mwcuBGTNNFjRQ86LOnAzbD0GsnmPkrIFXnCa01e42b4Tdbvf18TbgQ2wmWKgQdHE73ahAJWRjBGw3+T0hbzvCjelJl4tGMJEALLAp44z/b06BZNg6JLqOJ1ksCzTvQcXB3HTqu4eKcKXkWCKeISTvKuQ4k4O4O2yMjEhD4LcdzbgQ7Og+lefzUrfrgOaDH7Lp1iuHbhIdIUz/XrEBUF7m4mTNKAUSZdOiKQCEYvmstTC27a5rrnk8yR/EaHSh04NfoUc7vOZf/1/YzcMNLeJikhV+Q+scZY1pxZQwlHV55zM6IJuJFk3ucjq2bPjiVIXN4v4faWtD3zLEz6WXuuGQ5RpCZw1mGguwe01nfSvJy+0SwOXmxORHg8awO6cjm4EghJMdf76IQRgWTm+vd5tY31KlPbn41OB5XKR1HEOQxXxwh0R0YnfNBVKHGFm5fvAbB3/UmCbusZ8sQXfNJjPCDRCRMd6+7GwRBHymie/t87PPn++wz8DBQ46B14relrTGk/hfXn1rP2bEb+eHIPJeSKXGfLxS0cuHGAsQ0GUsTBKbGjUFIeBSUKdew9bP88ZWLIJLXYeWbS/ZJ2FpoDAwdiE6LIMEnj4ZeXmMMqJu0Re4+gIHB1MXEtpAIPIosjpZ6HUcUxST0SgSCef6/44+0RjDa1CUJoYl7EOZTxA/9geLf1hEd7YNDHYzKZ0Gq56Ll2r0JCg45dWx4ghOT9Z6Zx4EIzQFKt1BmOX6iAm2NYEsOTN82YOjUL43/cyMTczGtNX6OYczF6ruzJ1YfZ63aVHdQSfUWu4+niiUDw2ZHFLHLzoq57UbqWbcTgB7/gIqxKxt4P0ISwwzZzqMQpsT64pcaIY4mUiypZlqk7ltA+BBxLaKEasC1Va8a6s5BOZ+4s1DmE2ZOucOpaVf494U5cnInYWAMmKRACfH1h7lx45pkkA0waD797EJtiYYFf43P1NpdvzEr1ZyQxsOdsG4q53gcEDoZYKvtcpGGFf1lxYCDTl/bEwRCPb/HrBD0oS+nXbjF/zByKV6rJuuPPcfhH8weje4WEa5pMWgXHc7erm8U/rd+SBAQPH6Z1TA6SX8sKZLJol6uDK2v7reXp5U8zaM0g9ryyJw+NTUR55Ipc54lyT3BgyAGGNhxKk3KtOREVzcjDy+gd60985eHmFZ86wITRGEPwtfXccanMZf+lXKzyFpdqTuFRnYnaP1XsPVvRPD0TfnGHLU9otdAPj0h8tixs2fIE7Btk42kl6yx0dDy+sYv4+Y+q1HNfTFxMLNExBkwS9HrNY711C/r3T8Frt47PSyD0GAlerjRC7F1uXcnYhNjDqOI46GOpV+44QQ/KcuxqI34f25vYnS9T3tfIqE7fc2RKY0oWvU2fzz5jyOTeLFmqTyjb2+ap8kipZ+raDzl4/gkATFLQqfZm4k2O6dxdEhqqTZBmKMyUVXIpwyhLobKkZGHSvHWF1gxvPJy91/Yy+9BsouKisnDj7KHK2CryHCklH+/4mKl7ptK5cmecjFFcub2f4HhJiDHVwre4ObhhEAIPUyRNnSVPuupp5GSkgRMYBBiluYq4eb7QJCFWQoSE4jqtIa9WBtaBPe7/0ndYHYKOH0B3Zibc/INO0zZz4HwLirk95H54cWKNToCWptewkYGAAKhcWQvBTJqUxDiLh3luXoqNNMq9fpkbDyok265hVS0R8Ct5noEtlzOpz6fa5uJN2eN2iL59YdvXn/LaZ23593IjomJdETpBtWp6pk/XvinExmrNo+NjY7gd7IBOmMz55xlFYDBoq1r//ReqV0/n8Kx41qemayKOMcdK8sbFaQ1GXn0Vxo2DvXuhZ08ICMjAGKzJbJlhMwsCFiRMepZyL8WLpadxYMFg/juup2xZEn4/WSW9MrYqtKLIc4QQTGo3ieth19l8cTNerl74lWlNSxGNT/HaeHk1QC/0uDm6oRM6TNLEzbCb3H90n3hTPCEPzrD7xiFWB4cC4KXXpDDEqL1u7gzuArY+grvmAoRFdPCUq4mn3aCvexzNXD7FzXkpM9/ayDtPrWffubbsPdeKMsWCuB9ZAk+3BwSHl8TL/S5uzlE4RERSxL0WYWGGlPuBWioaxj6EwJnJdt96WCYjPxlAEh7rzc2wGlCkJtQYC1WHM6sP3LkDdQZ8YnuKSctj79kTbCdItQ+hzIm4do34eEGlSloD62QfWNakFYZIS+BTqXAYGAijRsGxY2Ra/FIMlXXPwBiSYpk0z+SH0wj/EYzwH8Geq3t4f/MnfP56azyaf85LS0NoHD+GgQPLZf5DJRMoIVfYBYPOwOJei7N8vpSSC/9O4dDhT9gUpQm3jwGux8E/MfDIBC2dwd8Z3AScjoV1kbAqAt4NgdeiD/DDjPlMmtSZ6X+Mo6znTT7u9Rmfr3+PUsVuceO+LwAPo4pRpeRFboeUwkHeJy7ag7LF7sKpn1P+R284A279DQ+P22wWwpRyirg2GqwX/Nx54MkPW/vxw9Z+KRwrsL2QrTdve82sc/t2Og2sIeUwhGW+IhWB18S6BceOhlHW+wHTJ97jGe8aCZPPr74Kmzdn3qPOUhPu1EipzHAGaV2hNdNr7KCXIZaGL2xn4fHd6HXzeaLDVVas8Mrch0omUEKuKJAIIaja+GOqepRk0NF3IT4MS3u2xA49aO+dvMGzAfLWZvZEw//dh0k3b6IX79JzqGSVh4nWLqA3OfDtlte4ed8Xd6cwomLciDE5c+1eOW4/LINJCnTCRL+S3eB4YOqTYV4tkgl5w4oBHL7UMo0RpSTOqY4+vR+P1XFZE/TwcPjzT1i1Kg3vOLXa4QlrAEzas1ngbcXawN693vTs6U1AUy1zKDsetXXJYYuYX7sG1aplafjZIigIKldwZOtLm7kZdpO2/2vL3rBl+F5/jdySXDXZqSjYVB0Oz4fCAAkDjDAgHmq+p3UCqvkeDDBBnzvQ4W9E0wW0qfQkG3st4MIbF3i7xdvsii9ClyAochGWRMax8d2niTcZuB/hZZZAyY375Yk36ZBSx1eD3qZGmZOkORmWQmnc38Y8n4lByVQeWSGxemLGj9e4fx/27EkjNTO13H2bNQAmLdx09wAHVywlIiyWCUMO4Hh+Oh3qHqB75xBWfLOHoDPnsuVRp1ZyuF9KX2pymKSTrJcuJX6oHL9znNCYUKJDvHEr8TDXbFBCrnj8aDgDnjmvPVtTdTh0+BuqDqdK8SrM7DyTG+/cZk3VqlRxgGHBUNr3OAFT/GlR7SBuTpG4Oj7C1TGKmmXOsnpsH97o8q35YiL1FaTeLcCplM2m8l63GNpuQTYHlpMCnxK2gu/pCatX23rHyUgpd9+S9mkh8EvY1p6gwxspV+QEuh3ttMnObe2oEL+Im4FnKXNjGNcvPsB0JzGD5do17dtARshUE+4cJKX1CNOmgd5gpMlLq3h6aU90VzvgcLE3r71SItfsUKEVRaHnQsXhnDv/LgD7oqGS12l2ftQuIfslOXrwG5ZifnoC9T41t7JL5Ptho/h+2CiGfT+fH3aOSPm8LJGamNvG3tMXfdsCXSEhsH+/tiXD3vHdA+ZuT9ZohV3KeN7g+j1fTPFx6HQSTCauhZSlWulzNKtyADeH+8wcu4F3vhTsO9ecdevg8OEM3NOMpeRwXmI9yRoVH8FVz1VQzYsg3XWC9tTGaU04xcs78t0yHTVr5p4d6XrkQghnIcQ/QojjQohTQohPk+wfJ4SQQgiv3DNTochZjCYji44uotqcary75V06+zbhFQ8YfBsaXYc612DKfVgTAWdiBfESwADebaDzHq2dW1oTYlWHa1knKfD9sFHIZTpebvNTrowtdTIaYkn09nft0kIqGfaOg3eaa+kkvbWBZn6HcXOKZOb694iLN7DzdDvWHe1BvxYrcTTEsfadZ9h0rDNe1RvkmUedXYKCwKn4HZ78uRNeM714de2ruHnfo1HJ5pz8x4voCGcCT+t49tnctSMjoZUYoIOUsj7QAHhKCNEcQAhRDugMXMs1CxWKHObvC39T77t6vLr2VUoXKc38p+fzSOfEojBo7QLzvMFDBx/fg963oOZVSambJejr0ItVZV7PeEZDj9NQ6slUd4dHF8mhEeUefmVvMX16JuLNPu1A55Bkow6qDMHRty1r3+nFpuNd8RoZwuifF7Nk1CvUKKMF32v7nmbXxC6EXjqqlQbOpvjlyAKhdIhzvcq1a5Izd88x0n8k2wZvo73nYHr4N6K2T+2cv2EqpBtakdqKIUsrFwfzw/Id7GvgPeDPXLFOochhjCYjPVb0IM4UR8tyLanhVYOxf43F1cGVxb0W82JpP8TdXYxyLMHd8KtccazM6XgDf1/8mxUnV/Db6d847HmYMkXKUKZIyrnhRpOR0JhQwmPCKd12HY56qxWVq0tDjFYcrFW1vaz+p28ujjYlDzxzmSynL5fi+p0olrw/mxphV+FuGuEkSGyld3omBK0DKUHvRGDcCEZ9XIljxyRlPW+y9LWhPPPe2wSe+4h2b07j2NmylPUJZfqnYTzjnX03PLvpjBkh3hTPUf134DiUTrc28/mbNdi3D9avh4kTc+YeGSVDKzuFEHrgCOAHfCulHC+EeAboKKUcI4S4AvhLKUNSOHc4MBygfPnyja9etV9hGYVCSsk7m99hwZEFRMVFUcy5GE9XfZovnvyCUu6l0jx39qHZjPlrTML7rn5dGVRvENHx0fxy6hcO3zzMo/hHRMdHJxxTvmh5VvRZwRPltOXyLE8U14hoV4oMsaRN5gwO+liMJgMmmfSaSUU9Y2Ju0MXRstp+dn7cXtugc0y312kCdw/A5SXExeuo0vcrDE5O3L8Xj5vTI4LuutvYJIRW/mDt2pwR2z17oG9fLfRhyYTp31+7bk7kci//bzmDfh+ERNKt6DjC18zk+DFB2bJa4bGcDqXkyMpOKaURaCCEKAasEULUAz4EUv/emHjuQmAhaEv0M3I/hSK3EELwVZevmNFpBuGx4Xg6eyJSn9W04Y2mb/BEuSe4GXaTE3dOMOvQLDZd2ARo3db71emHu6M7LgYXPF08cdA5MOvQLDov7cyGARto5+Zkcz135yje7zGN6es+yrHxxRsdMC3Tc+pGLTpM2UJweGnzHuuJT8ioZx5vcjBXZDRjiktc+JMallWdsQ/h4o/sPdmKoNt6Ph1/jeqNytO3b/KQkpSwfLkWAsn0aswUyNEFQikw6+AsJJI5XecwuslodGPt25Q5U1krUsqHQoidQE+gEnDc/E/gC/wrhGgqpbydxiUUinyBg96B4i7FM3WOEAL/Mv74l/GnZ42eTGg1gTMhZ3A2OFOleBVzLRdbnqv1HG3/15b2i9uzrWkPOiTZ36nudqav+4Cc88o1ca7te5o735Xlz4AevDBnJTHxLmRFzF0coqjtezpxg84h7aYd5xfC4VFYV8zZdaY1QkjG+A+iWN8dJC7cSs6pU9rk6qpV2atPktsLhMoELISF9XljEryBwMUFVq7MXj2V7JCRrBVvsyeOEMIF6AQclVL6SCkrSikrAjeARkrEFYUJB70DdUvWpWqJqimKOEBJ95JULFYRgH9D7ybbfzfMh9q+gVTxOZ/O3UwUcXqQrk3lS9jmHfT0X0f0YjfkMj3y0GhO7j5Gq/rnSOzOlLYnGW9yoF+LldobrzYph1UsVSXPL4QAWxG3ZtGf9TCZknSGSgGTCSIj4YUXslgfnuwtEEpvkjQkBP5cWB+EidffjqBbN3j0SAvlZNXe7JIRN6A0sEMIcQI4DGyRUq7PXbMUiseH3Vd307tmb97p8KXWYNqKMp5BhIR7ce7LGshluhQWDZl4r/sM5DIDV2ZXTvde814dncoeCRcWUPt6Y/a8V52TM+riXykAQQqpglZ8OfDthKwS7u1PfoB1SdqA17SuSGYCb9ag3ZQdfLHhXeKNBuZtGY1BH0/S+jBJI1sdO8JPP2kC3KFD1rJOsrpAKL2GI4GB1tcwUbXuAzZsAL1eCw+luGgqD0hXyKWUJ6SUDaWU9aSUdaSUk1M4pmJKE50KhQIalW7E5oubmXjqLy76LwWHYgn7mvkdSsitjo0z0PeJlbg7RxD4eU3kMh1ymYEZ/bUSr8XdQ/lq4NgU7qAtw3/v9SC6NT2ShiUSi7dc2/c0h6c0JXqxC2U9b5LSKtEPe06xWskKyPjkJQmsC2dZ5Y/HxRvo8eU6nqy7mdvzSuJVJJgzt2oQZ3TA9luATNaJfu9eePhQC4lImfUOTpYFQqGhZDid0XqBj6Oj7apWi8g7WLIri1/k3dElOXtW66dqNOZcDD6zqCX6CkUu88tzv9CqfCum7J6C37LnaXPXi1kP4H9h8F1EHK4DnuHjg11xGhFCl4XzeGrgYKq0767Vj0nyL/pWt9mcnFGHNjV24+ESRs0ygfz+uyZ4M+aUheeCofN+c7OO9CfgHA1x/D2hC7XLnk443qCL573uM5jyfJKSuegT4+OWcIpjicSmGiJxyu3gheZERLszocf/4e4cxc6POuBVRPP1hNUHSiKamBsM0KQJDBqkhVhKlUouqLlJWpOkFpFv1cq8I7oYVZqdZcUKiI7WvPKMlhTIadQSfYUilynrUZZNAzdxI+wGP5/4mf8d+x9v3UvcX9PnNCPGtqeYThIYp+e3CCP/7CnPW3G+DH0uFPfVXiBjEo6v7XuaXR+3095UGAgtf7a9oXcLaDzLXEo2mvQmNGv7nubkzLrpD8RvWMplahvNSmyv9+9YMEYT9KAM5Upc15bim+8xpN1P/Hu5IQcutCAilcVQZctCmzZw75428fnEE4n7cjLrJDXSmiS1iPycOfDbb0CUNx6PvPnpJ80b1+vzpkhXSighVyjyCF8PXya0msD4luO5E3mH6N3P43D/MGVKt0Z03Axoee4bzm/g8/2f89bfb/Hprk95pcFohoX+Sc34S1ZX00OFfslF3IKlMuHlJXDxR5BxmTPWrSroHSD8HCC1/HFLVcekdchj7yV2+ClWFy4vocy5c1y/Vw6TSSSI+bWQ8lQtdZ5YoxPHrjYwN/HwpEPt3ZwJf5rrt9y5dg1mzSKhv+hoq5B/XpSltZ4kfecd2LePhJovd+9qIu9SNBxafQN7P+TQIe1bjLOzlj5pr5ICqtWbQpFPOXTjEF8d/Io1gWuIM8XR2tuP4cWdea7BSJxrvJbxC1nndd/ZCff/Sfv4CgOhWG3b+uLWTTQy0A4t9uZBajavzrAXzvFO7yXs22egxydT8HS7z8iOCxj39BfsDRpKj09nUc43nnMXXalUSRPEGze0UJHJBMOHw5Ej2uPRI80bHp3afG4OceqUdg9LpyLLAp/YWKhR00TpNhvYX6437fUfc/iLTzh8OPcFPL0FQUgp8+zRuHFjqVAoMsediDty5t6Z0m+2n2QSstQXpeSP//4oTSZT1i4YvF/Knb2kXFNRe/zdRntsairlv+9JudJFymV67Tl4f+rXODkt9f1SypMnpWzTRkoPDylr1pRyyvtXZMniD6XxwKiE8/r1k/Kjj6SsXFnK6dOljI2VcscOKd3dpfz9dymdnaV0cpKyRg0pP/1U237mTNaGnV1uhN6QvhO6SCrslA6ukbJajXj5++95c28gQKahrUrIFYoCgtFklFsubpGtfmolmYTs/1t/eeXBFWk0GXPuJienaSK+DCmX67X3OcTKlVL6+9tuGz9eyqFDk4v+779LuXu3lCVLSmm0Gl6/flJOnJj4/vRpKdu2lbJoUSlr1ZJy7lzb93/+mX27T945Kbdf2i5b/dRKuk9zl3+d/yvrH6JZJD0hVzFyhaKAoBM6OlXuRIdKHZi+Zzqf7PyEFSdXUNOrJp+1/4zeNXtnuNxAqvi0A51ei2sIfdqrODNJWhOJKdUS/+WXtJfZJy2MtXMnPPUUjBmTc4WypJQ0XtiYGGMMeqHn+x7f08WvS9Yulouo9EOFooChEzo+bPMhx0ce5+suXyORPLfqOep/V5/FxxYTZ8zkxGZSpDmnPK35M0v64d0DqR+ThMyutrQWfguWuuiBgdC0qdZWbdky+OsvcHEBJyfw8MhcymJaKzkfRD8gxhiDp7Mn1966xisNX8nwePMSJeQKRQGljk8dxjYfy8lRJ1ncazESyct/vkyNb2uw++ruzF3MIsynZyZmuMg4LeslpWMtqzm3d8ywmGd2tWVqwt+nj+aJV68ODRsmLhYKCNDEOCgo8RrppSymt5Jz2YllgCbo2f6AzEWUkCsUBRy9Ts/g+oM5MfIE6/qvQy/0tF/cnok7JhJvik//AtbCfHNd+scnTT9MqQF1KmRmtWVqwv/wobYwZ9QoTaTbtYNGjWDcOLh9G374QVv2X7So1qourUU6aa3kBBjdZDTjWowD4Id/k7awyz8oIVcoHhOEEHSv1p1/R/zLi/VeZPLuybT7Xztuhd9K+0RrYUYCerRVnnrwbJj8eJ92ias5U2tAnUOkJPyWhTktWmge+5QpWv1xSwimXDntOSxM296sWerXT6/crV6np0+tPgBUK5HLSezZQAm5QvGY4e7ozv96/Y9lvZdx7PYxnln5DFFxUamfYC3Meieo+Y72Gqmt1Dy/0DYebllsVO+zFHPIcxtL7Nxg0Dz2JUtsw/khVlWfHB3h0KH0r5VSHN7CxvMbAahXsl4OjSDnUUKuUDymDKg7gBV9VnAk6AjD1g1L/cCkwuxYzKyMJjDGQMDryePh3i0SV3NmctIzu1jHzqtVg4oVE/c5O8MHH2getl6vhVjSipFnZAL264NfA3Dl4RWuhV7jZPBJ7j+6nytjyypqZadC8ZgzccdEJu+ezOFhh/Evk/riwASsV24izKVpzemIVYaBW/nEcIp1zZW0vHPL6lLrFaLZwHr1ZUREokft6amtwDQaISZGy2R59920Ow6ltpLTwh9n/qD/6v42LfwAOlXuxJoX1uDu6J7t8aRHeis7lZArFI85YTFhlPu6HN2qdmNFnwyWD7QIr6UQlimWwKDajPpxNseu1qds8SCmj9nFM2VeR6tkqIP6UxK99KTXyiXB37NHm5wMC9PeGwxQogTcuaO9d3LSBDq7S+gjYiPYcG4DtyNuU7pIaU4Fn+Kz3Z9R2bMye17ZQ+kipdO/SDbIkZ6dCoWi4OLh5MHwRsP5+uDX/F/H/6NCsQo2+wMD4fnn4eRJ660tzA8A67CMRCcktx+U5Nn3huPqNJDyJa4z/YX3eaZJiZQNSCnLJSWRzozgmwkK0uLcQmgeeHR0oog7OmrZJzlRB8Xd0Z0X6ryQuKG29jR592SWHF/C+Fbjs3+TbKBi5ApFIeDlBi9jlEbWnbNNL4yL0zza06e1MET9+knPTPqNXeDpFsL9SE8kghdb/sycl95g4LxlnD2byrf7jGa5ZCGtsUwZePAAiheHiRO1sEqH1g9xMMRzfMfRHO9mb41F2C89uJTOkbmPEnKFohBw4s4JAJqWbWqz/eBBrTyrlODuDsePW/Yk7xhk4V6EDzphpITbPQ5eaEaH2jvo3nAjK3Z1S/nmGc1yyYjgW/cHXeNLs8tOuMlL9Gy8lg1/hFGsqJGde4vw5YC3qHGtec5PwlqtaI2J12rE1y+V7NMvz1GhFYWiEGAy99J0Mbgkbrx7gKD1f+Ai3iJWXwyHuBAgYy1uTNJAvMlgbiokqFC1GDcflkv9BO8W6ce8LYKfWow8IfQSg6XDkKMB1r7Tg9GL5nHiqqSCTxBTn32TZ5v8oR1yeUnOpUdahX7mhOoYF6KFXLpX654z188GSsgVikJAw9Lawp6jt49St2RdTZS2tKKM0xM8iv2A2HhHgh6WydQ1Qx958ETVg6B35tr9KlQrtwfuGrInnGkJfkLoxbZNnE3HJNeKEHUl6/dPgdDoUCLjIjFd+ZOYRzEcijYxJthIBVdP9o74j7IedurvZoUScoWiEFC9RHVcHVwJCApgcP3B5viziWZ+hyjhHkJkjDtSZi7SqtMJRoxyZGfkL6zbWpLDn/WE7Zdzb5GQJfRi5ZEnw1rEhQNUGky8KZ6I2AjCY8IJjw1P/zk2POH4WxG3EsJS1hTXwVdt3ssXIg4q/VChKDR0W9aNY7ePcWT4EUpHX4EtWkPMUzdq8cLslZy6WSdT16tVS3DjBpT1CmHqMyN4tsnvWny73mcppyFmECklkXGRhEaHJhfakH+JuH+c8HsnCI+4TLiJlB8SwoUz4SaS5X+nhk7oKOJYhCJORRKePZw88C/tT8ViFdHr9OgiLlNHPKBxtQHoS7ZK/6I5hMojVygUAOy7to/OSzvjZHCiY6WODA7byDOujxL2L9nTj5e+W57K2bZ1zgcM0MrHAjYLiOKFA2Et/yDUvRqhMaGExYQRGh1KaEwoodHm95bXsSnvC4sJS4jpp4e7gCK6FB56PUV8e1CkqJ+NMFue3R3dk21zMbhkv557LqGEXKFQJHAm5Ayf7vqUlSdXUsenDv8VvwrGcGIl3I91oNzQB8SbXFM9X+hMCGGi0xfjkCUCE8U6KoTQmFCiMlDq1UHnQFHnong4eVDUqShFnYtS1Mn2vYeTR8IjqeAWcdSE2O3qMnRHXjOvPDVj3W80j2vA5CZqQZBCoUighlcNVvRZQaNSjXhv63sUDfXgUZyBOFM8EAcjm8KKNfCgqu2JhijQx4PHLYo+/TnXHPZTNKYoxZyLUb5oeU2ArUQ4pdcWsXY2OOeM51ttJHjW12qoPwqCKkOg6vDsX7cAojxyhaIQEh4TzpTdU4iKi8Ld0T3Zw83RLUUP2aBTvp89UB65QqFIRhGnIszoPMPeZihyCLWyU6FQKAo4SsgVCoWigKOEXKFQKAo4SsgVCoWigKOEXKFQKAo4SsgVCoWigKOEXKFQKAo4SsgVCoWigJOnKzuFEHeBq3l2w0S8gBA73DevKSzjBDXWx5HCMk7I/FgrSCm9U9uZp0JuL4QQAWktb31cKCzjBDXWx5HCMk7I+bGq0IpCoVAUcJSQKxQKRQGnsAj5QnsbkEcUlnGCGuvjSGEZJ+TwWAtFjFyhUCgeZwqLR65QKBSPLUrIFQqFooDzWAm5EKKvEOKUEMIkhPC32t5ZCHFECPGf+blDCueuFUKczFuLs05mxyqEcBVCbBBCnDGf93/2sz7jZOV3KoRobN5+QQgxW+TXjrpJSGOsJYQQO4QQEUKIuUnO6W8e6wkhxF9CCK+8tzzzZHGsjkKIhUKIc+a/4z55b3nmyMo4rY7JsCY9VkIOnAR6A7uTbA8Bekgp6wIvAUutdwohegMReWJhzpGVsX4hpawBNARaCiG65oml2SMr45wPDAeqmh9P5YGdOUFqY40GPgbGWW8UQhiAb4D2Usp6wAng9TywMyfI1FjNfAgESymrAbWAXblqYc6QlXFmWpMeq1ZvUspAIFljVynlUau3pwBnIYSTlDJGCOEOvI32j/9rXtmaXbIw1ihgh/mYWCHEv4BvHpmbZTI7TqA44CGlPGA+bwnQC9iUF/ZmhzTGGgnsFUL4JTlFmB9uQoh7gAdwIQ9MzTZZGCvAq0AN83EmCsAq0KyMMyua9Lh55BmhD3BUShljfv8Z8CUQZT+Tco2kYwVACFEM6AFss4dRuYD1OMsCN6z23TBve+yQUsYBo4D/gCA0L/VHuxqVS5j/ZgE+E0L8K4RYJYQoaU+bcpFMa1KB88iFEFuBUins+lBK+Wc659YGZgBPmt83APyklG8JISrmsKnZJifHarXdAKwAZkspL+WUrdkhh8eZUjw83+TYZmesKVzLAU3IGwKXgDnA+8CU7NqZE+TkWNG0yhfYJ6V8WwjxNvAF8GI2zcw2Ofw7bUAWNKnACbmUslNWzhNC+AJrgMFSyovmzS2AxkKIK2g/Cx8hxE4pZbucsDW75PBYLSwEzkspZ2XTvBwjh8d5A9uQkS+at5ovyOpYU6GB+ZoXAYQQvwITcvD62SKHx3oPzUNdY36/ChiSg9fPMjk8zixpUqEIrZi/lm0A3pdS7rNsl1LOl1KWkVJWBFoB5/KLiGeV1MZq3jcFKAqMzXvLcpY0fqe3gHAhRHNztspgILPeX0HhJlBLCGGpitcZCLSjPbmG1FYurgPamTd1BE7bzaBcIsuaJKV8bB7As2geWQxwB/jbvP0jIBI4ZvXwSXJuReCkvceQW2NF80wl2j+6ZftQe48jN36ngD9atsBFYC7mFcz5/ZHaWM37rgD30TIZbgC1zNtHmn+nJ9CEroS9x5GLY62Alv1xAm1+p7y9x5Eb47Tan2FNUkv0FQqFooBTKEIrCoVC8TijhFyhUCgKOErIFQqFooCjhFyhUCgKOErIFQqFooCjhFyhUCgKOErIFQqFooDz/7Z0UUjAYDhDAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Where in the state do we see Hispanic-heavy home districts?\n",
    "minHisp1 = 0.35\n",
    "minHisp2 = 0.45\n",
    "sumHispDistricts = 0.\n",
    "for t in range(nTracts):\n",
    "    if (HDvHisp[t] > minHisp1 and tractPop[t] > minTractPop):\n",
    "        sumHispDistricts += tractPop[t]/avgDistrictPop\n",
    "        if (HDvHisp[t] < minHisp2):\n",
    "            plt.scatter(tractCPx[t],tractCPy[t],marker='.',color='orange' )\n",
    "        else :            \n",
    "            plt.text(tractCPx[t],tractCPy[t],'o',color='blue', fontsize= 12)\n",
    "print(\"using a threshold of\",minHisp1,\"the number of Hisp districts should be\",round(sumHispDistricts,3))\n",
    "x,y = MAP.exterior.xy\n",
    "plt.plot(x,y,c=\"green\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "a92133ad-dc95-4aa1-af02-c1d71296cee6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this is a bar plot of seats by VAP pct Black for CA\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ALTERNATE VIEW OF BLACK VOTE: HOW MANY DISTRICTS PER 10pct BIN of PCT BLACK VOTE?\n",
    "n_bins = 10\n",
    "BlackSeats = [0.]*n_bins\n",
    "binMid = [0.]*n_bins\n",
    "for b in range(n_bins):\n",
    "    binMid[b]= float(b)/n_bins + 0.5/n_bins  #centering each bin\n",
    "for t in range(nTracts) :\n",
    "    b = int(HDvBlack[t]*n_bins)\n",
    "    BlackSeats[b] += HDweight[t]*nDistricts  #multiply by nDistricts to get number of expected seats\n",
    "\n",
    "print(\"this is a bar plot of seats by VAP pct Black for\",STATE)        \n",
    "fig, ax = plt.subplots()\n",
    "plt.bar(binMid,BlackSeats,width=0.09 )\n",
    "ax.set(xlabel=\"pct Black\", ylabel=\"number of seats\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "b1e9c437-ddf7-4202-aff0-19f338a5d013",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Black candidates would expect to win 2.588 OH seats out of 15\n",
      "Using simple Alabama-style of Blacks voting 0.9 Dem and whites voting 0.8 GOP\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Where in the state do we see opportunity home districts?  #NEW FORMULATION based on ALABAMA\n",
    "isOppor = [0]*nTracts #will track whether this is an opportunity district\n",
    "blackFracSeats = 0.\n",
    "blackPctDem = 0.9  #fraction of Black voters who are Democrats (est'd from Chen / Stephanopoulos)\n",
    "whitePctGOP = 0.8   #fraction of White voters who are Republican  (\"  \")\n",
    "#minBlack1 = 0.30\n",
    "#minBlack2 = 0.50\n",
    "for t in range(nTracts):\n",
    "    pctWhiteDem = (1-whitePctGOP)*(1-HDvBlack[t])  #this is the fraction of voters who are white Democrats\n",
    "    pctBlackDem = blackPctDem * HDvBlack[t]  #fraction of voters who are black Democrats\n",
    "    if tractPop[t] > minTractPop and HDvGOP[t] < 0.5 :  #Dems would win this Home District\n",
    "        if pctBlackDem > pctWhiteDem : #Blacks would win the primary\n",
    "            isOppor[t] = 1\n",
    "            plt.scatter(tractCPx[t],tractCPy[t],marker='.',color='blue' )\n",
    "            blackFracSeats += HDweight[t]\n",
    "        else :  #the White Dem candidate would win the election          \n",
    "            plt.scatter(tractCPx[t],tractCPy[t],marker='.',color='gray' )\n",
    "\n",
    "print(\"Black candidates would expect to win\",round(blackFracSeats*nDistricts,3),STATE,\"seats out of\",nDistricts)\n",
    "print(\"Using simple Alabama-style of Blacks voting\",blackPctDem,\"Dem and whites voting\",whitePctGOP,\"GOP\")\n",
    "x,y = MAP.exterior.xy\n",
    "plt.plot(x,y,c=\"green\")\n",
    "plt.show()\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "c5125128-e4bb-4337-bc5e-3f48d7cf404f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here's the state map with Hisp+Black greater than  0.4 or even 0.5\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Where in the state do we see Black+Hispanic heavy home districts?\n",
    "minMinor = 0.40 \n",
    "minMinor2 = 0.50\n",
    "print(\"Here's the\",STATE,\"map with Hisp+Black greater than \",minMinor,\"or even\",minMinor2)\n",
    "for t in range(nTracts):\n",
    "    if ((HDvBlack[t] + HDvHisp[t]) > minMinor and tractPop[t] > minTractPop):\n",
    "        if (HDvBlack[t] + HDvHisp[t]) > minMinor2 :\n",
    "            plt.scatter(tractCPx[t],tractCPy[t],marker='.',color='blue' )\n",
    "        else :            \n",
    "            plt.scatter(tractCPx[t],tractCPy[t],marker='.',color='gray' )\n",
    "\n",
    "x,y = tractMAP.exterior.xy\n",
    "plt.plot(x,y,c=\"green\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "58119ef8-13ef-4135-9843-6518025dda07",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this is a histogram of home-district population by tract; avg =  760350.3461538461\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# LET'S VISUALIZE OUR HOME DISTRICT population in a histogram\n",
    "n_bins=50\n",
    "print(\"this is a histogram of home-district population by tract; avg = \",np.sum(tractPop)/nDistricts)        \n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "# We can set the number of bins with the *bins* keyword argument.\n",
    "a = avgDistrictPop\n",
    "ax.hist(HDvPop, bins=[0.9*a,0.92*a,0.95*a,0.99*a,1.0*a,1.01*a,1.05*a,1.1*a])   #n_bins\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "1f9101bd-108a-48cb-bee5-3f4e04c18132",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this is a histogram of home-district area by tract\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# more HOME DISTRICT STATS in a histogram\n",
    "n_bins=50\n",
    "print(\"this is a histogram of home-district area by tract\")        \n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "# We can set the number of bins with the *bins* keyword argument.\n",
    "ax.hist(HDarea, bins=n_bins)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "d8167a80-2b91-4adc-ab34-9e010838213d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# What is the correlation of HD area to red-blue lean?\n",
    "fig, ax = plt.subplots()\n",
    "plt.scatter(HDarea,HDvGOP,marker='.' )\n",
    "ax.set(xlabel=\"tract area\", ylabel=\"home district pct GOP\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "cf95cc7c-e58a-4174-94f6-b6d4c7ccb0ff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# What is the correlation of tract usage to red-blue lean?\n",
    "fig, ax = plt.subplots()\n",
    "plt.scatter(HDvGOP,tractUse, marker='.' )\n",
    "ax.set(xlabel=\"home district pct GOP\", ylabel=\"tractUse\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "617384b8-1e0b-45a7-ae09-babe8dd9d429",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# What is the correlation of tract usage to tract population?\n",
    "fig, ax = plt.subplots()\n",
    "plt.scatter(tractPop,tractUse, marker='.' )\n",
    "ax.set(xlabel=\"Census tract population\", ylabel=\"tractUse\")\n",
    "ax.set_xlim(left=0,right=10000)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "91f163ab-6b94-47ee-bd29-be3e751fe2b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# UPDATED VOTES-SEATS CURVE (from votes2seats.ipynb 1/15/22)\n",
    "# LET'S REWORK OUR VOTES - SEATS CALCULATIONS\n",
    "# FIRST, LET'S DO THE BASIC VOTES-TO-SEATS, no fractional seats\n",
    "# INPUTS ARE HDvGOP[nTracts] and HDweight[nTracts]\n",
    "# HDvGOP is the redness lean of each Census tract's Home District\n",
    "# HDweight is the population of this Census tract relative to the state population\n",
    "# stateGOP is the statewide fraction of GOP vote vs. GOP + Dem vote\n",
    "# KEY EQUATION:\n",
    "# expected Seats at a given vote V = sum(HDweight) for tracts with HDvGOP > 0.5 + (V - stateGOP)\n",
    "# for easy calculation, create ~1000 bins, each bin containing HD's in a dV vote window\n",
    "nBins = 1000\n",
    "dV = 1./nBins\n",
    "binWeight = [0.]*nBins\n",
    "\n",
    "for t in range(nTracts):\n",
    "    binNo = int(HDvGOP[t]*nBins)   #which vote bin does this tract's vote go into for the expected statewide vote?\n",
    "    binWeight[binNo] += HDweight[t]\n",
    "    \n",
    "binVote = [0.]*nBins  #this will store the statewide vote for this bin\n",
    "for b in range(nBins) :\n",
    "    binVote[b] = b*dV\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "plt.plot(binVote, binWeight, marker='.',linestyle=\"none\")\n",
    "ax.set(xlabel=\"district pct GOP\", ylabel=\"bin weight\")\n",
    "plt.show()   #this should resemble above histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "85608d3f-c3bd-4d91-9378-16270ceeb9b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#continuing with votes-to-seats, let's compute the S(V) curve with no fractional-seat smearing\n",
    "cumVote = [0.]*nBins\n",
    "for b in range(nBins) :\n",
    "    cumVote[nBins-b-1] = np.sum(binWeight[:(b+1)])  #cumulative weight of all Home Districts below vote b*dV\n",
    "    # print(\"bin, bin vote, cumVote for this bin\",b,b*dV,cumVote[b] )\n",
    "    \n",
    "cumSeats = [0.]*nBins  #this will sum the seats earned for a given statewide vote\n",
    "stateVoteBin = int( (stateGOP+0.5*dV)*nBins )   #which bin (out of 1/dV) holds the statewide total vote?\n",
    "for b in range(nBins) :\n",
    "    bb = int( max(0,min(nBins-1,nBins/2 + b-stateVoteBin)) )\n",
    "    cumSeats[b] = 1. - cumVote[bb]\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "plt.plot(binVote, cumSeats, marker='.',linestyle=\"none\")\n",
    "ax.set(xlabel=\"statewide vote, nBins =\"+str(nBins)+\",\"+str(STATE), ylabel=\"GOP seats won (no fractl smearing)\")\n",
    "RANGE = [0.1, 0.9]\n",
    "fifty50 = [0.5, 0.5]\n",
    "expected = [stateGOP, stateGOP]\n",
    "plt.plot(RANGE,fifty50)\n",
    "plt.plot(fifty50,RANGE)\n",
    "plt.plot(expected,RANGE, linestyle=\"--\",color='red')\n",
    "\n",
    "#LET'S ALSO crudely ESTIMATE RESPONSIVENESS near the STATEWIDE VOTE, with a pseudonormal weighting and lst-sq fit\n",
    "stateSigma = 0.03  #User-adjustable, this is the uncertainty in the statewide vote from election to election\n",
    "usedBins = int(stateSigma/dV)\n",
    "nFitPoints = 6*usedBins\n",
    "voteData = [0.]*nFitPoints\n",
    "seatData = [0.]*nFitPoints\n",
    "counter = 0\n",
    "for b in range(nBins):\n",
    "    if ( abs(b-stateVoteBin) <= 2*usedBins ):  #include this S-V pair in our line fit\n",
    "        voteData[counter]=binVote[b]\n",
    "        seatData[counter]=cumSeats[b]\n",
    "        counter += 1\n",
    "        # print(b,counter)\n",
    "        if ( abs(b-stateVoteBin) < usedBins) : #double count this in data set\n",
    "            voteData[counter]=binVote[b]\n",
    "            seatData[counter]=cumSeats[b]\n",
    "            counter +=1\n",
    "fit = np.polyfit(voteData,seatData,1)  #first-order linear regression with old polyfit\n",
    "Rsimple = fit[0]     #slope is fit[0] in y = mx + b, intercept is fit[1]\n",
    "y0 = fit[1]\n",
    "Rx = [stateGOP - 4.*stateSigma, stateGOP + 4.*stateSigma]\n",
    "Ry = [y0 + Rx[0]*Rsimple, y0 + Rx[1]*Rsimple]\n",
    "plt.plot(Rx,Ry ) \n",
    "ax.text(Rx[1]+0.02, Ry[1]+0.02, \"R = \"+str(round(Rsimple,4)), transform=ax.transAxes, fontsize=14,color='purple')\n",
    "expectedSeats = cumSeats[stateVoteBin]\n",
    "ax.text(0.02,expectedSeats+0.03,\"expected seats = \"+str(round(expectedSeats,3)),transform=ax.transAxes,fontsize=9)\n",
    "ax.text(stateGOP+0.01,0.1,\"HD statewide vote = \"+str(round(stateGOP2,3)),transform=ax.transAxes,fontsize=9)\n",
    "Ex = [0,stateGOP ]\n",
    "Ey = [expectedSeats, expectedSeats]\n",
    "plt.plot(Ex,Ey, linestyle='-.',color='red')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "ce47266f-e2ea-4649-b10c-e8225994c122",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#3/6/22 - alternate votes-to-seats with fractional seat smearing.\n",
    "# First, compute the general cdf sliver for -3 sigma to +3 sigma\n",
    "# Then, apply this smearing to the binVote weights\n",
    "seatVar = 0.04\n",
    "nBins = 1000\n",
    "nSigma = 6.  #how many total sigma of deviation we are explicitly modeling; the rest go into the tails\n",
    "nSlivers = 2*int(3*nBins*seatVar)  #budget for 3 sigma on either side of the expected vote\n",
    "sliverWt = [0.]*nSlivers  #each sliver holds the cdf reflecting the relative distance from the mean vote\n",
    "sliverSigma = [0.]*nSlivers\n",
    "totalSliverWt = 0.\n",
    "for nS in range(nSlivers):\n",
    "    dSigmaHigh = nSigma* (nS+0.5 - nSlivers/2) / float(nSlivers)\n",
    "    dSigmaLow =  nSigma* (nS-0.5 - nSlivers/2) / float(nSlivers)\n",
    "    sliverSigma[nS] = 0.5*(dSigmaHigh+dSigmaLow)  #for plotting; keeps track of this sliver's center sigma\n",
    "    sliverWt[nS] = norm.cdf(dSigmaHigh) - norm.cdf(dSigmaLow)\n",
    "    totalSliverWt += sliverWt[nS]\n",
    "lowSliverWt = 0.5 * (1. - totalSliverWt)\n",
    "highSliverWt = lowSliverWt\n",
    "#print(\"each tail of distribution has weight\",round(lowSliverWt,4) )\n",
    "#plt.plot(sliverSigma,sliverWt)\n",
    "#plt.show()\n",
    "# OK, that worked as expected.  Now, do the smearing of each bin\n",
    "smearedBinWeight = [0.]*nBins\n",
    "for b in range(nBins):\n",
    "    centerBinNo = b #int(HDvGOP[t]*nBins)   #which vote bin does this tract's vote go into for the expected statewide vote?\n",
    "    binOffset = int(nSlivers/2)\n",
    "    for nS in range(nSlivers):\n",
    "        binNo = centerBinNo + nS - binOffset\n",
    "        if (binNo < 0): #deep blue district; variance would push vote %R < 0\n",
    "            binNo = 0\n",
    "        if (binNo >= nBins):  #deep red district; variance would push vote %R > 1\n",
    "            binNo = nBins - 1\n",
    "        smearedBinWeight[binNo] += binWeight[b]*sliverWt[nS]\n",
    "    # Now put the tails into the correct bins\n",
    "    binNo = centerBinNo -1 - binOffset  #left tail\n",
    "    if binNo < 0:\n",
    "        binNo = 0\n",
    "    smearedBinWeight[binNo] += binWeight[b]*lowSliverWt\n",
    "    binNo = centerBinNo + nSlivers - binOffset  #right tail\n",
    "    if binNo >= nBins:\n",
    "        binNo = nBins -1 \n",
    "    smearedBinWeight[binNo] += binWeight[b]*highSliverWt\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "plt.plot(binVote, binWeight, marker='.',linestyle=\"none\",label=\"unsmeared\")\n",
    "plt.plot(binVote, smearedBinWeight, marker='o',linestyle=\"none\",label=\"smeared\")\n",
    "RANGE = [0.0, 0.5*np.max(binWeight)]\n",
    "sGOP = [stateGOP, stateGOP]\n",
    "plt.plot(sGOP,RANGE,linestyle=\"-\",label=\"statewide \"+str(round(stateGOP,3)) )\n",
    "ax.set(xlabel=\"district pct GOP\", ylabel=\"bin weight\")\n",
    "plt.legend()\n",
    "plt.show()   #this should resemble above histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "8a2d7de3-ea93-4447-bb69-36defbae38df",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#continuing with votes-to-seats, let's compute the S(V) curve with no fractional-seat smearing\n",
    "smearedBinVote = [0.]*nBins  #this will store the statewide vote for this bin\n",
    "cumSmearedVote = [0.]*nBins\n",
    "for b in range(nBins) :\n",
    "    smearedBinVote[b] = b*dV\n",
    "    cumSmearedVote[nBins-b-1] = np.sum(smearedBinWeight[:(b+1)])  #cumulative weight of all Home Districts below vote b*dV\n",
    "    # print(\"bin, bin vote, cumVote for this bin\",b,b*dV,cumVote[b] )\n",
    "    \n",
    "cumSmearedSeats = [0.]*nBins  #this will sum the seats earned for a given statewide vote\n",
    "stateVoteBin = int( (stateGOP+0.5*dV)*nBins )   #which bin (out of 1/dV) holds the statewide total vote?\n",
    "for b in range(nBins) :\n",
    "    bb = int( max(0,min(nBins-1,nBins/2 + b-stateVoteBin)) )\n",
    "    cumSmearedSeats[b] = 1. - cumSmearedVote[bb]\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "plt.plot(smearedBinVote,cumSmearedSeats, marker='o',linestyle=\"none\",label=str(seatVar)+\" smear\")\n",
    "plt.plot(binVote, cumSeats, marker='.',linestyle=\"none\",label=\"no smear\")\n",
    "ax.set(xlabel=\"true \"+STATE+\"-wide vote=\"+str(round(stateGOP,4))+\", nBins =\"+str(nBins), ylabel=\"GOP seats won\")\n",
    "RANGE = [0.1, 0.9]\n",
    "fifty50 = [0.5, 0.5]\n",
    "expected = [stateGOP, stateGOP]\n",
    "expectedSeats = cumSeats[stateVoteBin]\n",
    "expectedS = [expectedSeats,expectedSeats]\n",
    "smearedSeats = cumSmearedSeats[stateVoteBin]\n",
    "smearedS = [smearedSeats,smearedSeats]\n",
    "plt.plot(RANGE,fifty50)\n",
    "plt.plot(fifty50,RANGE)\n",
    "plt.plot(RANGE,smearedS, linestyle=\"--\",color='blue',label=str(round(expectedSeats,3))+\"no smear\")\n",
    "plt.plot(RANGE,expectedS, linestyle=\"--\",color='orange',label=str(round(smearedSeats,3))+\"smeared\")\n",
    "plt.plot(expected,RANGE, linestyle=\"--\",color='red')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "597b7758-4f83-40f7-8909-4946e64267ad",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "simpler and fractional-seat-smeared (var of 0.04 ) responsiveness are 2.395 2.196\n",
      "fractional expected GOP seats =  6.661  out of  52 seats for CA\n",
      "simpler expected GOP seats =  5.9635  out of  52 seats\n"
     ]
    }
   ],
   "source": [
    "#Finally, let's compare responsiveness using smeared (fractional seat variance) to non-smeared calculated above\n",
    "#LET'S ALSO crudely ESTIMATE (smeared) RESPONSIVENESS near the STATEWIDE VOTE, as we did for non-smeared\n",
    "stateSigma = 0.03  #User-adjustable, this is the uncertainty in the statewide vote from election to election\n",
    "usedBins = int(stateSigma/dV)\n",
    "nFitPoints = 6*usedBins\n",
    "voteData = [0.]*nFitPoints\n",
    "seatData = [0.]*nFitPoints\n",
    "counter = 0\n",
    "for b in range(nBins):\n",
    "    if ( abs(b-stateVoteBin) <= 2*usedBins ):  #include this S-V pair in our line fit\n",
    "        voteData[counter]=smearedBinVote[b]\n",
    "        seatData[counter]=cumSmearedSeats[b]\n",
    "        counter += 1\n",
    "        # print(b,counter)\n",
    "        if ( abs(b-stateVoteBin) < usedBins) : #double count this in data set\n",
    "            voteData[counter]=smearedBinVote[b]\n",
    "            seatData[counter]=cumSmearedSeats[b]\n",
    "            counter +=1\n",
    "fit = np.polyfit(voteData,seatData,1)  #first-order linear regression with old polyfit\n",
    "Rsmeared = fit[0]     #slope is fit[0] in y = mx + b, intercept is fit[1]\n",
    "y0 = fit[1]\n",
    "\n",
    "print(\"simpler and fractional-seat-smeared (var of\",seatVar,\") responsiveness are\",round(Rsimple,3) ,round(Rsmeared,3) )   \n",
    "print(\"fractional expected GOP seats = \",round(nDistricts*smearedSeats,3),\" out of \",nDistricts,\"seats for\",STATE)\n",
    "print(\"simpler expected GOP seats = \",round(nDistricts*expectedSeats,4),\" out of \",nDistricts,\"seats\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "86f82727-7193-4194-aa61-2b99408dbcb6",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "language": "python",
   "name": "python3"
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    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "pygments_lexer": "ipython3",
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